{
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  "sourcesContent": ["import{jsx as e,jsxs as t}from\"react/jsx-runtime\";import{ComponentPresetsConsumer as n,Link as a}from\"framer\";import{motion as i}from\"framer-motion\";import*as o from\"react\";import{Youtube as r}from\"https://framerusercontent.com/modules/NEd4VmDdsxM3StIUbddO/1de6WpgIbCrKkRcPfQcW/YouTube.js\";export const richText=/*#__PURE__*/t(o.Fragment,{children:[/*#__PURE__*/e(\"h2\",{children:\"Predictive maintenance\"}),/*#__PURE__*/e(\"p\",{children:\"Human health and safety on a construction project is of utmost importance, but maintaining the \u201Chealth\u201D of on-site equipment is another critical task for construction managers.\"}),/*#__PURE__*/t(\"p\",{children:[\"According to a \",/*#__PURE__*/e(a,{href:\"https://www.mckinsey.com/business-functions/operations/our-insights/manufacturing-analytics-unleashes-productivity-and-profitability\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"study by McKinsey\"})}),\":\"]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/e(\"p\",{children:\"Predictive maintenance can reduce machine downtime by 30-50% and increase its lifespan by 20-40%.\\xa0\"})}),/*#__PURE__*/e(\"p\",{children:\"Replacing construction equipment is costly, and machines that aren\u2019t functioning further cost a project time and money. Predictive maintenance aims to avoid these two issues by assessing the condition of equipment, which allows for maintenance before a problem occurs that may interrupt work.\"}),/*#__PURE__*/e(\"p\",{children:\"The earlier a defect or issue is detected, the better the chance that it can be resolved before causing bigger problems.\"}),/*#__PURE__*/e(\"p\",{children:\"As with other issues in construction, humans are capable of performing inspections and detecting issues, but they can\u2019t accomplish this reliably 24/7.\"}),/*#__PURE__*/e(\"p\",{children:\"Luckily, AI and machine learning can.\"}),/*#__PURE__*/e(\"p\",{children:\"When machine learning systems are trained on large amounts of historical data, they can begin to predict when and what kind of maintenance will be necessary for a given set of equipment.\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Read \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/quality-training-data-for-machine-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"An Introductory Guide to Quality Training Data for Machine Learning.\"})})]})}),/*#__PURE__*/e(\"img\",{alt:\"Remote vehicle monitoring for predictive maintenance\",className:\"framer-image\",src:\"https://framerusercontent.com/images/BiJSsdMR48IV22tAuY8210xMUY.png\",srcSet:\"https://framerusercontent.com/images/BiJSsdMR48IV22tAuY8210xMUY.png?scale-down-to=512 512w,https://framerusercontent.com/images/BiJSsdMR48IV22tAuY8210xMUY.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/BiJSsdMR48IV22tAuY8210xMUY.png 1197w\"}),/*#__PURE__*/e(\"p\",{children:\"Pairing this with the Internet of Things (IoT) sensors not only helps an AI model detect defects more accurately, but also provides additional training for better predictions.\"}),/*#__PURE__*/e(\"p\",{children:\"It\u2019s not all just a matter of observing the equipment, though. Machine learning models make their predictions using classification and regression models. Classification models can help predict the possibility that a machine will break down after a certain number of steps (actions or uses). Regression models can generate predictions on how much time is left before equipment maintenance is needed.\"}),/*#__PURE__*/e(\"p\",{children:\"Since properly functioning equipment is central to making progress on a construction project, being able to predict when it will need maintenance helps solve business problems and streamline decision-making.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Explore how \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-manufacturing\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"AI is used in predictive maintenance in manufacturing.\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"Of course, construction managers are still the ones who will check this data and make the decisions, but consistent, data-driven predictions will only help them do this better.\"}),/*#__PURE__*/e(\"h2\",{children:\"Labor efficiency monitoring\"}),/*#__PURE__*/e(\"p\",{children:\"Measuring labor efficiency is a complex process.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Current methods are costly, time-consuming, and require significant labor themselves. And ultimately, the results are not all that reliable.\"}),/*#__PURE__*/e(\"p\",{children:\"For example, it\u2019s hard enough to track and measure the productivity of one worker, but when teams cooperate to accomplish a task, the assessment of productivity becomes all the more convoluted.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"As a result, construction managers tend to assess labor efficiency only when a noticeable problem arises. So in general, there are many, many opportunities for improved efficiency that are entirely neglected.\"}),/*#__PURE__*/e(\"p\",{children:\"Ai-powered computer vision, however, can make this job a whole lot easier.\"}),/*#__PURE__*/e(\"p\",{children:\"Construction sites usually have several cameras installed to monitor the area. When these cameras are coupled with computer vision systems, they are capable of monitoring worker activity using techniques like object detection and human pose estimation.\"}),/*#__PURE__*/e(\"img\",{alt:\"Worker activity monitoring using computer vision\",className:\"framer-image\",src:\"https://framerusercontent.com/images/oK4OEjZ5XcW1iyxUWina8s30uRs.png\",srcSet:\"https://framerusercontent.com/images/oK4OEjZ5XcW1iyxUWina8s30uRs.png?scale-down-to=512 512w,https://framerusercontent.com/images/oK4OEjZ5XcW1iyxUWina8s30uRs.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/oK4OEjZ5XcW1iyxUWina8s30uRs.png 1156w\"}),/*#__PURE__*/e(\"p\",{children:\"Still, it\u2019s not a simple task. Background clutter, occlusions, and uniformed workers who look similar to each other can make tracking difficult.\"}),/*#__PURE__*/t(\"p\",{children:[\"Nevertheless, researchers in \",/*#__PURE__*/e(a,{href:\"https://www.construction.cam.ac.uk/files/erini_web.pdf\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"this case study\"})}),\" decided to give it a go. They proposed a framework in which labor productivity of construction workers could be measured by tracking their trajectory using on-site cameras.\"]}),/*#__PURE__*/e(\"p\",{children:\"Computer vision algorithms then process this data, tracking worker location over time and generating a 4D trajectory that can be converted into productivity data.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"While working in 4D may sound a bit sci-fi, the framework turned out to be quite successful when tested on real-life data. When observing and assessing single and multiple workers on the job, the framework managed to determine worker time-on-task with 95% accuracy!\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Looking for quality data? Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/computer-vision-datasets\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"20+ Open Source Computer Vision Datasets.\"})})]})}),/*#__PURE__*/t(\"p\",{children:[\"Similarly, \",/*#__PURE__*/e(a,{href:\"https://www.icevirtuallibrary.com/doi/pdf/10.1680/jsmic.20.00014\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"another paper\"})}),\" describes how computer vision models can extract 3D worker trajectories from visual data and use a clustering-based method to generate work cycles that represent labor input.\\xa0\"]}),/*#__PURE__*/e(\"img\",{alt:\"3D trajectory calculation\",className:\"framer-image\",src:\"https://framerusercontent.com/images/TXr5CPkGDNAN9GAMuDST4Qo42M.png\",srcSet:\"https://framerusercontent.com/images/TXr5CPkGDNAN9GAMuDST4Qo42M.png 514w\"}),/*#__PURE__*/e(\"p\",{children:\"When tested, this method was able to determine time-on-task in a construction project with 84% accuracy. Sure, improvements can be made, but considering humans\u2019 limited ability to track time-on-task across an entire job site for multiple workers, the numbers are looking pretty good!\"}),/*#__PURE__*/e(\"h2\",{children:\"Land survey and mapping\"}),/*#__PURE__*/t(\"p\",{children:[\"So fa,r we\u2019ve looked at how AI can help track, measure, and inspect the people and things \",/*#__PURE__*/e(\"em\",{children:\"inside \"}),\"a construction site.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"But what about surveying the work site itself?\"}),/*#__PURE__*/e(\"p\",{children:\"Getting an accurate lay of the land is crucial to a successful construction project\u2014not only for better pre-construction planning but also for ensuring that construction is going according to plan.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"To help with this, companies like \",/*#__PURE__*/e(a,{href:\"https://www.datumate.com/about-us/\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Datumate\"})}),\" do land surveys and mapping using AI-powered drone and camera technology.\"]}),/*#__PURE__*/e(\"p\",{children:\"A good example of this is their product DatuFly. \"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.datumate.com/products/datufly/\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"DatuFly\"})}),\" captures images of land, construction sites, and infrastructure and then uploads them to a secure server. Next, the computer vision and photogrammetry algorithms convert the images into accurate, georeferenced 2D and 3D maps and models.\"]}),/*#__PURE__*/e(\"p\",{children:\"Of course, land surveying is something humans have done for centuries, and can do pretty well. But the modern accessibility of UAVs and computer vision techniques can make this process a whole lot easier by reducing the time needed and increasing accuracy.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"AI in construction planning represents a major benefit to project managers and workers because faster, more accurate mapping means more efficient construction processes.\"}),/*#__PURE__*/e(\"h2\",{children:\"Building the Future with AI\"}),/*#__PURE__*/e(\"p\",{children:\"Construction managers have a full plate when it comes to overseeing a building project. But from increasing job site safety to asset inspection and productivity measurements, AI/ML-powered computer vision can make overseeing such a complex task much easier, faster, and more accurate.\"}),/*#__PURE__*/e(\"p\",{children:\"When the use of AI in construction can be leveraged to support planning and decision making, decrease project costs, and save worker lives, everyone wins. \"}),/*#__PURE__*/e(\"p\",{children:\"And with more data and training, smart computer vision technologies stand to continue transforming the efficiency and safety of the whole construction industry.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Curious to learn more? Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/computer-vision-applications\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"27+ Most Popular Computer Vision Applications and Use Cases\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"Interested in learning how computer vision can support your construction projects? \"}),/*#__PURE__*/t(\"p\",{children:[\"\u200D\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/get-started\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Schedule a demo\"})}),\" with our team at V7 to get started!\"]}),/*#__PURE__*/e(\"p\",{children:\"Check out next:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-healthcare\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"7 Life-Saving AI Use Cases in Healthcare\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-retail\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"6 AI Applications Shaping the Future of 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Dentistry\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-transportation\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"9 Revolutionary AI Applications In Transportation\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-supply-chain-and-logistics\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"AI in Supply Chain and Logistics [20+ Practical 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\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/medical-image-annotation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"medical imaging\"})}),\", autonomous vehicle tracking, and more.\"]}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"em\",{children:\"So much more...\"}),/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"In this article, we'll cover everything you need to know about object tracking. You are also invited to check out our bonus V7 tutorial on\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/training\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" building your own object tracking models\"})}),\" from scratch. \"]}),/*#__PURE__*/e(\"p\",{children:\"Here\u2019s what we\u2019ll cover:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"What is Object Tracking?\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Object Tracking vs. Object Detection\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"4 stages of the Object Tracking process\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Levels of Object Tracking\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Object Tracking challenges\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Deep Learning-based approaches to Object Tracking\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Visual Object Tracking with V7 (Tutorial)\"})})]})]});export const richText2=/*#__PURE__*/t(o.Fragment,{children:[/*#__PURE__*/t(\"p\",{children:[\"And in case you\u2019d like to jump right into the deep end of the pool and start building your own AI models, check out:\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/model-management\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"V7 Model Training\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/workflows\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"V7 Workflows\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/auto-annotation\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"V7 Auto Annotation\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/dataset-management\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"V7 Dataset Management\"})}),/*#__PURE__*/e(\"em\",{children:/*#__PURE__*/e(\"br\",{})})]})})]}),/*#__PURE__*/e(\"h2\",{children:\"What is Object Tracking?\"}),/*#__PURE__*/t(\"p\",{children:[\"Object tracking is a \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/deep-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"deep learning\"})}),\" process where the algorithm tracks the movement of an object. In other words, it is the task of estimating or predicting the positions and other relevant information of moving objects in a video.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"Object tracking usually involves the process of \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/object-detection-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"object detection\"})}),\". Here\u2019s a quick overview of the steps:\"]}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Object detection, where the algorithm classifies and detects the object by creating a bounding box around it.\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Assigning unique identification for each object (ID).\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[\"Tracking the detected object as it moves through frames while storing the relevant information.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]})})]}),/*#__PURE__*/e(\"p\",{children:\"Have a look at this video to see how V7 handles object tracking.\"}),/*#__PURE__*/e(\"div\",{className:\"framer-text-module\",style:{\"--aspect-ratio\":\"560 / 315\",aspectRatio:\"560 / 315\",height:\"auto\",width:\"100%\"},children:/*#__PURE__*/e(n,{componentIdentifier:\"module:NEd4VmDdsxM3StIUbddO/1de6WpgIbCrKkRcPfQcW/YouTube.js:Youtube\",children:t=>/*#__PURE__*/e(r,{...t,play:\"Off\",shouldMute:!0,thumbnail:\"Medium Quality\",url:\"https://www.youtube.com/watch?v=_3DlSkseiRw\"})})}),/*#__PURE__*/e(\"p\",{children:\"Object Tracking vs. Object detection\"}),/*#__PURE__*/e(\"p\",{children:\"Object tracking refers to the ability to estimate or predict the position of a target object in each consecutive frame in a video once the initial position of the target object is defined.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"On the other hand, object detection is the process of detecting a target object in an image or a single frame of the video. Object detection will only work if the target image is visible on the given input. If the target object is hidden by any interference it will not be able to detect it.\"}),/*#__PURE__*/e(\"p\",{children:\"Object tracking is trained to track the trajectory of the object despite the occlusions.\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Read \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/yolo-object-detection\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"YOLO: Real-Time Object Detection Explained.\"})})]})}),/*#__PURE__*/e(\"h3\",{children:\"Types of Object Tracking\"}),/*#__PURE__*/e(\"p\",{children:\"There are two types of object tracking: image tracking and video tracking.\\xa0\"}),/*#__PURE__*/e(\"h4\",{children:/*#__PURE__*/e(\"strong\",{children:\"Image tracking\"})}),/*#__PURE__*/e(\"p\",{children:\"Image tracking is the task of automatically recognizing and tracking the images.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"It is mostly applied in the field of augmented reality (AR). For instance, when given a two-dimensional image as an input through a camera, the algorithm detects two-dimensional planar images, which can be then used to superimpose a 3D graphical object.\"}),/*#__PURE__*/e(\"p\",{children:\"Once the 3D graphic is superimposed, the user can move the camera without actually losing track of the 2D planar surface and graphic on top of it.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"Companies like Apple and Ikea use such technologies to give the customers a virtual experience of how their products will look in their personal settings.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"img\",{alt:\"Ikea image tracking for an armchair for Augmented Reality experience\",className:\"framer-image\",src:\"https://framerusercontent.com/images/2Cfycqc5FdsK54DvXOjLXQldo.png\",srcSet:\"https://framerusercontent.com/images/2Cfycqc5FdsK54DvXOjLXQldo.png?scale-down-to=512 512w,https://framerusercontent.com/images/2Cfycqc5FdsK54DvXOjLXQldo.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/2Cfycqc5FdsK54DvXOjLXQldo.png 1600w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://techcrunch.com/2017/09/12/ikea-place-the-retailers-first-arkit-app-creates-lifelike-pictures-of-furniture-in-your-home/\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:/*#__PURE__*/e(\"em\",{children:\"Source\"})})})}),/*#__PURE__*/e(\"h3\",{children:/*#__PURE__*/e(\"strong\",{children:\"Video tracking\"})}),/*#__PURE__*/t(\"p\",{children:[\"Video tracking is the task of tracking a moving object in a video.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"The idea of video tracking is to associate or establish a relationship between target objects as it appears in each video frame. In other words, video tracking is analyzing the video frames sequentially and stitching the past location of the object with the present location by predicting and creating a bounding box around it.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"p\",{children:\"Video tracking is widely used in traffic monitoring, self-driving cars, and security because it can process real-time footage.\"}),/*#__PURE__*/e(\"h2\",{children:\"4 stages of the Object Tracking process\"}),/*#__PURE__*/e(\"p\",{children:\"Now, let\u2019s discuss the object tracking process in more detail.\"}),/*#__PURE__*/e(\"h3\",{children:\"Target initialization\"}),/*#__PURE__*/t(\"p\",{children:[\"The first step involves defining the object of interest or targets.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"It incorporates the process of \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/bounding-box-annotation\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"drawing a bounding box\"})}),\" around it in the initial frame of the video. The tracker must then estimate or predict the object\u2019s position in the remaining frames while simultaneously drawing the bounding box simultaneously.\\xa0\"]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Looking for the perfect bounding box tool? Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/bounding-box-annotation-tool-features\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"9 Essential Features for a Bounding Box Annotation Tool.\"})})]})}),/*#__PURE__*/e(\"h3\",{children:\"Appearance modeling\"}),/*#__PURE__*/t(\"p\",{children:[\"Appearance modeling deals with modeling the visual appearance of the object. When the targeted object passes through various scenes like the lighting condition, angle, speed, etc., they may change the appearance of the object, and it may lead to misinformation and the algorithm losing track of the object.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"Appearance modeling has to be conducted so that modeling algorithms can capture various changes and distortions introduced when the target object moves.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"img\",{alt:\"Appearance modeling distortions and challenges in object tracking\",className:\"framer-image\",src:\"https://framerusercontent.com/images/vKGhDzwvyEDftDW0NFDMBk1l0.png\",srcSet:\"https://framerusercontent.com/images/vKGhDzwvyEDftDW0NFDMBk1l0.png?scale-down-to=512 512w,https://framerusercontent.com/images/vKGhDzwvyEDftDW0NFDMBk1l0.png 998w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://arxiv.org/pdf/1303.4803.pdf\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:/*#__PURE__*/e(\"em\",{children:\"Source\"})})})}),/*#__PURE__*/e(\"p\",{children:\"Appearance modeling consists of two components:\\xa0\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Visual representation\"}),\": it focuses on constructing robust features and representation that can describe the object\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Statistical modeling\"}),\": it uses statistical learning techniques to build mathematical models for object identification effectively.\"]})})]}),/*#__PURE__*/e(\"h3\",{children:\"Motion estimation\"}),/*#__PURE__*/e(\"p\",{children:\"Motion estimation usually infers the predictive capability of the model to predict the object\u2019s future position accurately.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"Target positioning\"}),/*#__PURE__*/e(\"p\",{children:\"Motion estimation approximates the possible region where the object could most likely be present. Once the location of the object is approximated, we can then use a visual model to lock down the exact location of the target.\"}),/*#__PURE__*/e(\"h2\",{children:\"Levels of Object Tracking\"}),/*#__PURE__*/e(\"p\",{children:\"Object tracking can be defined by two levels:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Single Object Tracking(SOT)\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Multiple Object Tracking(MOT): it aims to track objects of multiple classes as we see in self-driving cars.\\xa0\"})})]}),/*#__PURE__*/e(\"h3\",{children:\"Single Object Tracking\"}),/*#__PURE__*/t(\"p\",{children:[\"Single Object Tracking (SOT) aims to track an object of a single class instead of multiple objects. It is also sometimes referred to as \",/*#__PURE__*/e(\"em\",{children:\"Visual Object Tracking.\\xa0\"})]}),/*#__PURE__*/e(\"p\",{children:\"In SOT, the bounding box of the target object is defined in the first frame. The goal of the algorithm is then to locate the same object in the rest of the frames.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"SOT belongs to the category of detection-free tracking because one has to manually provide the first bounding box to the tracker. This means that Single Object Trackers should be able to track whatever object they are given, even an object on which no available classification model was trained.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Learn more by reading \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/image-classification-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Image Classification Explained: An Introduction.\"})})]})}),/*#__PURE__*/e(\"h3\",{children:\"Multiple Object Tracking\"}),/*#__PURE__*/e(\"p\",{children:\"Multiple Object Tracking (MOT) refers to the approach where the tracking algorithm tracks every single object of interest in the video.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Initially, the tracking algorithm determines the number of objects in each frame, following that it keeps track of each object\u2019s identity from one frame to the next frame until they leave the frame.\\xa0\"}),/*#__PURE__*/e(\"h2\",{children:\"Object tracking challenges (and solutions)\"}),/*#__PURE__*/e(\"p\",{children:\"There are several challenges that one might face while working on object tracking algorithms.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Firstly, it is easy to track an object on a straight road or in a simple environment.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"We have already discussed how important it is to accurately model the target object. In a real-world scenario, the target object will go through deformation, occlusion, background noise, etc.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Let's explore some of the common issues that arise in object tracking.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"Occlusion\"}),/*#__PURE__*/e(\"p\",{children:\"The occlusion of objects in videos is one of the most common challenges.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"It refers to an interference phenomenon where the object is affected by the background or foreground in which the tracking algorithm loses track of the object. In other words, the algorithm gets confused as multiple objects come closer. This leads to the issue where the initially identified object is again (mistakenly) tracked as a new object.\"}),/*#__PURE__*/e(\"p\",{children:\"One can implement occlusion sensitivity to prevent it. Occlusion sensitivity allows the user to identify which particular feature of the object is confusing the network. Once identified, similar images can be used to correct the biases and help the network to extract features that differentiate the objects.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"Background clutter\"}),/*#__PURE__*/t(\"p\",{children:[\"In any \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/machine-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"machine learning\"})}),\" or deep learning task, the background of the images fed into the algorithm creates a lot of issues. It is the same with object tracking models.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"In theory, the more densely populated the background, the more difficult it is to extract features, detect or even track the object of interest.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"A densely populated background introduces redundant information or noise that makes the network less receptive to features that are important; they also make the network slow to learn and optimize.\\xa0\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"To prevent background clutter, one can use a well-curated dataset that has a sparse background.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Looking for quality data? Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/best-free-datasets-for-machine-learning\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"65+ Best Free Datasets for Machine Learning.\"})})]})}),/*#__PURE__*/e(\"h3\",{children:\"Training and Tracking Speed\"}),/*#__PURE__*/e(\"p\",{children:\"The modern deep learning algorithms have become much more complex, which means they can extract features and make meaningful correlations; this, in turn, also means that they consume more energy and time.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The tracking algorithm is not a single task algorithm, as we see in image classification and object detection. It is a multitask algorithm that performs object detection, localization, classification and also keeps track of the objects. This type of algorithm is mathematically complex, and it takes a lot of time to train.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"We must also keep in mind that the tracking algorithms must perform quickly during the inference time to yield accurate results. Enhancing tracking speed is especially imperative for real-time object tracking models.\"}),/*#__PURE__*/t(\"p\",{children:[\"To enable faster inference time, the model needs to be carefully designed or chosen. A \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/convolutional-neural-networks-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"convolutional neural network\"})}),\", which is the primary architecture for computer vision tasks, can be used in object tracking. These networks are capable enough to perform with great accuracy if designed carefully.\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[\"Some of the common algorithms used for tracking objects are Fast R-CNN and Faster R-CNN and their variants. These networks have been proven very efficient in the task of object tracking.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Learn more by reading \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/neural-network-architectures-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"The Essential Guide to Neural Network Architectures.\"})})]})}),/*#__PURE__*/e(\"h3\",{children:\"Varying spatial scales\"}),/*#__PURE__*/e(\"p\",{children:\"One of the issues with object tracking is that the target objects can vary in shape and size; with such a variety of information, the learning algorithm can get confused, leading to generalization error.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Below is the list of techniques that can help to tackle the issue of varying spatial scales:\"}),/*#__PURE__*/e(\"h4\",{children:/*#__PURE__*/e(\"strong\",{children:\"Anchor Boxes\"})}),/*#__PURE__*/t(\"p\",{children:[\"These are the predefined measurement of the target object. The boxes are meant to acquire the scale and aspect ratios of target objects. These boxes are fed into the network during \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/training\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"training\"})}),\", and it allows the network to learn and understand the position and size of the object.\"]}),/*#__PURE__*/t(\"p\",{children:[\"Anchor boxes also allow the network to detect multiple objects if they are overlapping by separately evaluating features and yielding accurate results.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"img\",{alt:\"Anchor boxes in object tracking \",className:\"framer-image\",src:\"https://framerusercontent.com/images/9TRXIQVFdrnr8da782eBIVoheSk.png\",srcSet:\"https://framerusercontent.com/images/9TRXIQVFdrnr8da782eBIVoheSk.png?scale-down-to=512 512w,https://framerusercontent.com/images/9TRXIQVFdrnr8da782eBIVoheSk.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/9TRXIQVFdrnr8da782eBIVoheSk.png 1356w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://towardsdatascience.com/5-significant-object-detection-challenges-and-solutions-924cb09de9dd\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:/*#__PURE__*/e(\"em\",{children:\"Source\"})})})}),/*#__PURE__*/e(\"h3\",{children:/*#__PURE__*/e(\"strong\",{children:\"Feature extraction\"})}),/*#__PURE__*/e(\"p\",{children:\"Features extraction is an important process in all deep learning techniques.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"It enables neural networks to understand the data fed into them. The convolutional neural network (CNN) used for object tracking and other computer vision tasks can efficiently extract spatial information.\"}),/*#__PURE__*/e(\"p\",{children:\"These networks, however, must be able to extract multi-scale spatial information. At times, when the object is smaller in the given input image, the network may lose too much signal during downsampling or as the signal propagates through the network. As a result, the network will not be able to detect and track smaller objects during the inference.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"To tackle such a situation, one should use or develop a network that can preserve the information extracted from each layer so that the network can detect objects within multiple CNN layers, including earlier layers where higher resolution remains.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/neural-networks-activation-functions\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"12 Types of Neural Network Activation Functions: How to Choose?\"})})]})})]});export const richText3=/*#__PURE__*/t(o.Fragment,{children:[/*#__PURE__*/e(\"h2\",{children:\"Deep Learning-based approaches to Object Tracking\"}),/*#__PURE__*/e(\"p\",{children:\"Object tracking has been around for almost 20 years now and a lot of methods and ideas were introduced to improve the accuracy and efficiency of the tracking models.\"}),/*#__PURE__*/e(\"p\",{children:\"Some of the methods involved traditional or classical machine learning approaches like k-Nearest Neighbor or Support Vector Machine. These approaches are good in predicting the target object, but they require important and discriminatory features extracted by professionals.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"On the other hand, deep learning methods extract these important features and representations by themselves.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Let\u2019s discuss some of the deep learning algorithms that are used in the task of object tracking.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"MDNet\"}),/*#__PURE__*/e(\"p\",{children:\"Multi-Domain Net is a type of object tracking algorithm which leverages large-scale data for training. Its objective is to learn vast variations and spatial relationships.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"MDNet is trained to learn the shared representation of targets from multiple annotated videos, meaning it takes multiple annotated videos belonging to different domains.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"MDNet consists of pretraining and online visual tracking:\"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Pretraining\"}),\": In pretraining, the network is required to learn multi-domain representation\",/*#__PURE__*/e(\"strong\",{children:\". \"}),\"To achieve this, the algorithm is trained on multiple annotated videos to learn representation and spatial features.\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Online visual tracking\"}),\": Once pre-training is done, the domain-specific layers are remove,d and the network is only left with shared layers, which consist of learned representations. During the inference, a binary classification layer is added, which is trained or fine-tuned online.\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[\"This technique saves time as well as it has proven to be an effective online-based tracking algorithm.\\xa0\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"img\",{alt:\"MDNet architecture\",className:\"framer-image\",src:\"https://framerusercontent.com/images/twBfb7n9l3nHGdKvgA7teMaI.png\",srcSet:\"https://framerusercontent.com/images/twBfb7n9l3nHGdKvgA7teMaI.png?scale-down-to=512 512w,https://framerusercontent.com/images/twBfb7n9l3nHGdKvgA7teMaI.png 701w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://arxiv.org/pdf/1510.07945.pdf\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:/*#__PURE__*/e(\"em\",{children:\"Source\"})})})}),/*#__PURE__*/e(\"h3\",{children:\"GOTURN\"}),/*#__PURE__*/t(\"p\",{children:[\"Deep Regression Networks are offline training-based models. This algorithm learns a generic relationship between object motion and appearance and can be used to track objects that do not appear in the training set.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"Online tracker algorithms are slow and do not perform well in real-time; this is because they cannot take advantage of a large number of videos to improve their performance. Offline tracker algorithms, on the other hand, can be trained to handle rotations, changes in viewpoint, lighting changes, and other complex challenges.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"Generic Object Tracking Using Regression Networks or GOTURN uses a regression-based approach to tracking objects. Essentially, they regress directly to locate target objects with just a single feed-forward pass through the network.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"The network takes two inputs: a search region from the current frame and a target from the previous frame. The network then compares these images to find the target object in the current image.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"img\",{alt:\"GOTURN architecture\",className:\"framer-image\",src:\"https://framerusercontent.com/images/EJiXFbskVToaOdBV7TnqoTQl6WI.png\",srcSet:\"https://framerusercontent.com/images/EJiXFbskVToaOdBV7TnqoTQl6WI.png?scale-down-to=512 512w,https://framerusercontent.com/images/EJiXFbskVToaOdBV7TnqoTQl6WI.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/EJiXFbskVToaOdBV7TnqoTQl6WI.png 1600w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://davheld.github.io/GOTURN/GOTURN.pdf\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:/*#__PURE__*/e(\"em\",{children:\"Source\"})})})}),/*#__PURE__*/e(\"h3\",{children:\"ROLO\u2014Recurrent YOLO\"}),/*#__PURE__*/t(\"p\",{children:[\"ROLO is a combination of \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/recurrent-neural-networks-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"recurrent neural networks\"})}),\" and YOLO. Generally, LSTM is preferred in combination with CNN.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"ROLO combines two types of neural networks: one is CNN which is used to extract spatial information while the other is an LSTM network which is used for finding the trajectory of the target object.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"At each time step, spatial information is extracted and sent to the LSTM, which then returns the location of the tracked object.\"}),/*#__PURE__*/e(\"img\",{alt:\"Recurrent YOLO (ROLO) achitecture\",className:\"framer-image\",src:\"https://framerusercontent.com/images/YZ1AhlvCYZ0b9QbifpODxv7JBU.png\",srcSet:\"https://framerusercontent.com/images/YZ1AhlvCYZ0b9QbifpODxv7JBU.png?scale-down-to=512 512w,https://framerusercontent.com/images/YZ1AhlvCYZ0b9QbifpODxv7JBU.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/YZ1AhlvCYZ0b9QbifpODxv7JBU.png 1600w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://arxiv.org/pdf/1607.05781v1.pdf\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:/*#__PURE__*/e(\"em\",{children:\"Source\"})})})}),/*#__PURE__*/e(\"p\",{children:\"We can use the above diagram to understand how ROLO works:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The video sequence is fed into the YOLO architecture which is primarily made of CNN, here features are extracted as well as bounding boxes are detected.\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The visual features and bounding boxes are then concatenated and fed to the LSTM\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The LSTM then predicts the trajectory of the objects.\"})})]}),/*#__PURE__*/e(\"h3\",{children:\"DeepSORT\"}),/*#__PURE__*/e(\"p\",{children:\"DeepSORT is one of the most popular object tracking algorithms. It is an extension to Simple Online Real-time Tracker or SORT, which is an online-based tracking algorithm.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"SORT is an algorithm that uses the Kalman filter for estimating the location of the object given the previous location of the same. The Kalman filter is very effective against the occlusions.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"SORT comprises of three components:\"}),/*#__PURE__*/e(\"ol\",{children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Detection: \"}),\"Detecting the object of interest in the initial stage i.\\xa0\\xa0\"]})})}),/*#__PURE__*/e(\"ol\",{start:\"2\",children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Estimation: \"}),\"Predicting the future location i+1 of the object from the initial stage using the Kalman filter. It is worth noting that the Kalman filter just approximates the object\u2019s new location, which needs to be optimized.\\xa0\"]})})}),/*#__PURE__*/e(\"ol\",{start:\"3\",children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Association\"}),\": As the Kalman filter estimates the future location of the object i+1, it needs to be optimized using the correct position. This is usually done by detecting the position of the object in that position i+1. The problem is solved optimally using the Hungarian algorithm.\"]})})}),/*#__PURE__*/e(\"p\",{children:\"With the basics of SORT out of the way, we can incorporate deep learning techniques to enhance the SORT algorithm. Deep neural networks allow SORT to estimate the object\u2019s location with much higher accuracy because these networks can now describe the features of the target image.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Essentially, the CNN classifier is trained on a task-specific dataset until it achieves good accuracy. Once it is achieved, the classifier is stripped, and we are left with only the features extracted from that dataset. This extracted feature is then incorporated with the SORT algorithm to track objects.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"SiamMask\"}),/*#__PURE__*/e(\"p\",{children:\"SiamMask aims to improve the offline training procedure of the fully-convolutional Siamese network. Siamese networks take in two inputs: a cropped image and a larger search image to obtain a dense spatial feature representation.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"The Siamese network yields one output. It measures the similarity of two input images and determines whether or not the same objects exist in the two images. This framework is very efficient for object tracking by augmenting their loss with a binary segmentation task.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"img\",{alt:\"SiamMask\",className:\"framer-image\",src:\"https://framerusercontent.com/images/gT5FazcyHXPH7s4Xhfs9Ufwm8E.png\",srcSet:\"https://framerusercontent.com/images/gT5FazcyHXPH7s4Xhfs9Ufwm8E.png?scale-down-to=512 512w,https://framerusercontent.com/images/gT5FazcyHXPH7s4Xhfs9Ufwm8E.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/gT5FazcyHXPH7s4Xhfs9Ufwm8E.png 1294w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"em\",{children:\"SiamMask\"})}),/*#__PURE__*/t(\"p\",{children:[\"Once trained, SiamMask solely relies on a single bounding box initialization and operates online yielding object segmentation masks.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/image-segmentation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"A Gentle Introduction to Image Segmentation for Machine Learning.\"})})]})}),/*#__PURE__*/e(\"h3\",{children:\"JDE (Joint Detection and Embedding)\"}),/*#__PURE__*/t(\"p\",{children:[\"\u200B\u200BJoint Detection and Embedding (JDE) is a single-shot detector designed to solve a multi-task learning problem. JDE learns target detection and appearance embedding in a shared model.\\xa0\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/t(\"p\",{children:[\"JDE uses Darknet-53 as the backbone to obtain feature representation at each layer. These feature representations are then fused using up-sampling and residual connections. The prediction heads are then attached on top of the fused feature representation, which yields a dense prediction map.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"img\",{alt:\"JDE architecture\",className:\"framer-image\",src:\"https://framerusercontent.com/images/njaMuksXg4MNcuvac86iOJuh9Xw.png\",srcSet:\"https://framerusercontent.com/images/njaMuksXg4MNcuvac86iOJuh9Xw.png?scale-down-to=512 512w,https://framerusercontent.com/images/njaMuksXg4MNcuvac86iOJuh9Xw.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/njaMuksXg4MNcuvac86iOJuh9Xw.png 1320w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"em\",{children:\"JDE architecture\"})}),/*#__PURE__*/e(\"p\",{children:\"To perform object tracking, JDE yields bounding boxes classes and appearance embedding from the prediction head. These appearance embeddings are compared to embeddings of previously detected objects using an affinity matrix.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Finally, the Hungarian algorithm and the Kalman filter are used for smoothing out the trajectories of the target object and as well as estimating the locations of the same.\"}),/*#__PURE__*/e(\"h3\",{children:\"Tracktor++\"}),/*#__PURE__*/e(\"p\",{children:\"Tracktor++ is an online tracking algorithm. It uses an object detection method to perform tracking by training a neural network only on the task of detection.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"It essentially predicts the position of an object in the next frame by calculating the bounding box regression. It doesn't perform any training or optimization on tracking data.\\xa0\\xa0\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The object detector for Tracktor++ is usually Faster R-CNN with 101-layer ResNet and FPN. It extracts features from the current frame by using the regression branch of Faster R-CNN.\\xa0\"}),/*#__PURE__*/e(\"h2\",{children:\"Visual Object Tracking using V7 [Tutorial]\"}),/*#__PURE__*/e(\"p\",{children:\"Now, let us briefly walk you through the process of Visual Object Tracking using V7.\"}),/*#__PURE__*/e(\"p\",{children:\"If you haven\u2019t done it yet, make sure to request a 14-day free trial before reading further.\\xa0\"}),/*#__PURE__*/e(\"ol\",{children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Upload data\"}),/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]})})}),/*#__PURE__*/e(\"img\",{alt:\"\",className:\"framer-image\",src:\"https://framerusercontent.com/images/1Vj55lUJN3ZQePOHmxjiqac8.png\",srcSet:\"https://framerusercontent.com/images/1Vj55lUJN3ZQePOHmxjiqac8.png?scale-down-to=512 512w,https://framerusercontent.com/images/1Vj55lUJN3ZQePOHmxjiqac8.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/1Vj55lUJN3ZQePOHmxjiqac8.png?scale-down-to=2048 2048w,https://framerusercontent.com/images/1Vj55lUJN3ZQePOHmxjiqac8.png 2221w\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"em\",{children:\"V7 Datasets tab\"})}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-cleaning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Data Cleaning Checklist: How to Prepare Your Machine Learning Data.\"})})]})}),/*#__PURE__*/e(\"ol\",{start:\"2\",children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"strong\",{children:\"Auto-annotate your data\"})})})}),/*#__PURE__*/t(\"p\",{children:[\"Once your video is uploaded, you can then \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-annotation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"start annotating the video\"})}),\". You can use V7\u2019s auto-annotation tool to speed up the process.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]}),/*#__PURE__*/e(\"img\",{alt:\"V7 dashboard for video annotation\",className:\"framer-image\",src:\"https://framerusercontent.com/images/EuhK0oUSQznPUv7tlMOFUwjwvUY.png\",srcSet:\"https://framerusercontent.com/images/EuhK0oUSQznPUv7tlMOFUwjwvUY.png?scale-down-to=512 512w,https://framerusercontent.com/images/EuhK0oUSQznPUv7tlMOFUwjwvUY.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/EuhK0oUSQznPUv7tlMOFUwjwvUY.png 1600w\"}),/*#__PURE__*/e(\"p\",{children:\"In this example, we will be tracking the runner with the white shirt. This video is a perfect example of object tracking, as the object tracking camera is very constant and focused on the runner.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: Read \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-labeling-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"What is Data Labeling and How to Do It Efficiently [Tutorial].\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"Select the desired frame in the video to start annotating. You can use the timeline bar at the bottom to navigate yourself to the desired frame.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Once you have selected the desired frame, create a polygon around the object of interest using the auto annotation tool.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Make sure that you select the instance ID as the subtypes. You can activate it by heading to the Classes tab in your dataset, editing or creating one, and adding Instance ID as a Subtype.\"}),/*#__PURE__*/e(\"img\",{alt:\"V7 annotation attributes\",className:\"framer-image\",src:\"https://framerusercontent.com/images/w1OHBehM9Ryoz58nyyuvVB26c.png\",srcSet:\"https://framerusercontent.com/images/w1OHBehM9Ryoz58nyyuvVB26c.png?scale-down-to=512 512w,https://framerusercontent.com/images/w1OHBehM9Ryoz58nyyuvVB26c.png 762w\"}),/*#__PURE__*/e(\"h3\",{children:\"Instance ID\"}),/*#__PURE__*/t(\"p\",{children:[\"You must have noticed that the select object is given an ID number; this is known as \",/*#__PURE__*/e(\"strong\",{children:\"instance ID\"}),\".\"]}),/*#__PURE__*/e(\"p\",{children:\"Instance ID keeps the track of an object throughout the video. This is very useful if the object changes its orientation; the instance ID can help to classify and detect it as the same object in multiple frames.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"Adding and deleting anchor points\"}),/*#__PURE__*/e(\"p\",{children:\"V7 allows you to add and delete anchor points to extend and delete the segmentation mask.\"}),/*#__PURE__*/e(\"img\",{alt:\"V7 auto-annotation on a marathon runner\",className:\"framer-image\",src:\"https://framerusercontent.com/images/pn1FE2yKDYFsAh2w96Sxwb3s9Qw.png\",srcSet:\"https://framerusercontent.com/images/pn1FE2yKDYFsAh2w96Sxwb3s9Qw.png?scale-down-to=512 512w,https://framerusercontent.com/images/pn1FE2yKDYFsAh2w96Sxwb3s9Qw.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/pn1FE2yKDYFsAh2w96Sxwb3s9Qw.png 1600w\"}),/*#__PURE__*/e(\"p\",{children:\"As you can see, the auto annotation tool automatically creates a segmentation around the selected object, in this case, our runner.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"You will also notice that the segmentation mask is missing in some areas. To rectify this, you can hover to the area where the segmentation mask is missing and extend it to the desired area within the polygon. Click on the areas where the segmentation mask is missing to complete the segmentation.\\xa0\"}),/*#__PURE__*/e(\"img\",{alt:\"V7 polygon mask correction on a marathon runner\",className:\"framer-image\",src:\"https://framerusercontent.com/images/yxJGnJPE3qqht1NDm5ldWbqZSEI.png\",srcSet:\"https://framerusercontent.com/images/yxJGnJPE3qqht1NDm5ldWbqZSEI.png?scale-down-to=512 512w,https://framerusercontent.com/images/yxJGnJPE3qqht1NDm5ldWbqZSEI.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/yxJGnJPE3qqht1NDm5ldWbqZSEI.png 1600w\"}),/*#__PURE__*/e(\"p\",{children:\"As you can see from the image above, I have extended the segmentation and have tried to mask the runner\u2019s body.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The green dots indicate the manual extension or addition of the segmentation, while red dots indicate the deletion of segmentation masks from some area. Once done, go to the next frame.\"}),/*#__PURE__*/e(\"p\",{children:\"To annotate the same object in the next frame, click on the rerun button on top of the polygon mask around the object. V7 will automatically cover the object with the segmentation mask.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"That\u2019s all. You can continue annotating your object in the subsequent frames by copying the instances and adjusting the label to the object until \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/when-to-annotate-data\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!1,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"you\u2019ve annotated all the instances.\"})})]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Pro tip: If you are looking for a free image annotation tool, check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/cvat-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"The Complete Guide to CVAT\u2014Pros & Cons.\"})})]})}),/*#__PURE__*/e(\"h2\",{children:\"Object Tracking: Key Takeaways\"}),/*#__PURE__*/e(\"p\",{children:\"Finally, here are some of the key takeaways from this article:\"}),/*#__PURE__*/e(\"p\",{children:\"1. Object tracking is a technique of tracking single or multiple objects independent of the frames.\"}),/*#__PURE__*/e(\"p\",{children:\"2. Object detection depends on the target object on every single frame while object tracking estimates the position of the target object in the next frame.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"3. There are two types of object tracking:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Image tracking\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Video tracking\"})})]}),/*#__PURE__*/e(\"p\",{children:\"4. There are four stages of object tracking:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Target initialization\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Appearance modeling\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Motion estimation\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Target positioning\"})})]}),/*#__PURE__*/e(\"p\",{children:\"5. Deep learning techniques such as deep neural networks allow deeper and meaningful extraction of information allowing traditional machine learning algorithms, like SORT, Kalman filters, etc. to work much more efficiently to estimate the position of the objects.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"6. You can use \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/best-image-annotation-tools\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"data annotation tools\"})}),\" like V7 to annotate your objects and train object tracking algorithms in less than an hour. \"]}),/*#__PURE__*/e(\"p\",{children:\"Got questions? Get in touch with our team to discuss them!\"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Read more:\"}),/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-preprocessing-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!1,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"\u200D\"})})]}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-preprocessing-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"A Simple Guide to Data Preprocessing in Machine Learning\"})})}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/train-validation-test-set\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"The Train, Validation, and Test Sets: How to Split Your Machine Learning Data\"})})}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-science-interview-questions-and-answers\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Supervised vs. Unsupervised Learning: What\u2019s the Difference?\"})})}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-science-interview-questions-and-answers\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"40+ Data Science Interview Questions and Answers\"})}),\"\u200D\"]}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/semi-supervised-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"The Ultimate Guide to Semi-Supervised Learning\"})})}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/mean-average-precision\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Mean Average Precision (mAP) Explained: Everything You Need to Know\"})})}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/contrastive-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"The Beginner\u2019s Guide to Contrastive Learning\"})})}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/reinforcement-learning-applications\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"9 Reinforcement Learning Real-Life Applications\"})})}),/*#__PURE__*/e(\"p\",{children:\"\u200D\"})]});export const richText4=/*#__PURE__*/t(o.Fragment,{children:[/*#__PURE__*/e(\"p\",{children:\"Here's a couple of interesting facts\u2014\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.fortunebusinessinsights.com/artificial-intelligence-ai-in-manufacturing-market-102824\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Reports\"})}),\" have shown that the global AI manufacturing market is expected to reach \",/*#__PURE__*/e(\"strong\",{children:\"$9,890,000,000 USD\"}),\" by 2027.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[\"Research suggests that European manufacturers are already embracing the AI surge, with \",/*#__PURE__*/e(a,{href:\"https://www.fortunebusinessinsights.com/artificial-intelligence-ai-in-manufacturing-market-102824\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!1,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"69% of German manufacturers\"})}),\" saying they are \",/*#__PURE__*/e(\"strong\",{children:\"ready to implement some form of AI\"}),\" in their operations soon.\\xa0\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[\"The European Commission estimated that as much as \",/*#__PURE__*/e(a,{href:\"https://ec.europa.eu/programmes/horizon2020/en/news/intelligent-approach-zero-defect-manufacturing\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"50% of production\"})}),\" in some industries can be dispensed with altogether \",/*#__PURE__*/e(\"strong\",{children:\"because of defects.\\xa0\"})]})})]}),/*#__PURE__*/t(\"p\",{children:[\"Defect detection, predictive maintenance, liquid level analysis, asset inspection are all being shaped by AI solutions based on \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/what-is-computer-vision\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"computer vision\"})}),\" and \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/machine-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"machine learning.\"})})]}),/*#__PURE__*/e(\"p\",{children:\"This ushers in a new epoch of manufacturing\u2014Industry 4.0\u2014which removes the need for time-consuming and tedious checks and replaces them with computer vision systems ensuring higher levels of quality control on the production assembly line.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"This is key because AI can spot defects that are otherwise easy to miss with the naked eye.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Here\u2019s what we\u2019ll cover:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Defect inspection\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Quality assurance\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Product assembly\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"PPE detection\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Reading text and barcodes\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Inventory management\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Predictive maintenance\"})})]}),/*#__PURE__*/e(\"p\",{children:\"We\u2019ll also be highlighting a number of current AI use cases in manufacturing, and describing how companies use training data platforms (such as V7) to train and deploy AI models.\"})]});export const richText5=/*#__PURE__*/t(o.Fragment,{children:[/*#__PURE__*/e(\"h2\",{children:\"Defect Inspection\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Quality control was Henry Ford\u2019s dream over a hundred years ago. But because the traditional assembly line has always relied on human beings to do their bit, it\u2019s always been at the mercy of human error.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The naked eye can only see so much.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Fortunately, AI can see so much more.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"Computer vision helps manufacturers with detection inspection via automated optical inspection (AOI). Using multi-cameras, it more easily identifies missing pieces, dents, cracks, scratches and overall damage, with the images spanning \",/*#__PURE__*/e(\"em\",{children:\"millions\"}),\" of data points, depending on the capability of the camera.\\xa0\"]}),/*#__PURE__*/e(\"img\",{alt:\"Missing pill detection using bounding boxes in V7\",className:\"framer-image\",src:\"https://framerusercontent.com/images/2v7CJ7WmrtU7yGBneTEvk3bm7I.png\",srcSet:\"https://framerusercontent.com/images/2v7CJ7WmrtU7yGBneTEvk3bm7I.png?scale-down-to=512 512w,https://framerusercontent.com/images/2v7CJ7WmrtU7yGBneTEvk3bm7I.png 1013w\"}),/*#__PURE__*/t(\"p\",{children:[\"Companies are already adopting AI visual inspection. For instance,\",/*#__PURE__*/e(a,{href:\"https://cloud.google.com/blog/products/ai-machine-learning/fih-mobile-automates-mobile-handset-defect-detection-with-ai\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!1,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" FIH Mobile\"})}),\" are using it in smartphone manufacturing to highlight defects.\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[\"Using computer vision to spot defects has numerous benefits. It allows for the \",/*#__PURE__*/e(\"em\",{children:\"early\"}),\" detection of defects, and it also lets manufacturers gather multiple statistics that will help them improve their assembly lines going forward.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"Ultimately, computer vision will reduce the margin of error and waste, while saving time and money.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Learn more about\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/model-management\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" training defect inspection models with V7.\"})}),\"\u200D\"]})}),/*#__PURE__*/t(\"p\",{children:[\"Various defect inspections that AI can carry out include using techniques such as template matching, pattern matching, and statistical pattern matching. Inspections are fast and accurate, and the AI also has the ability to learn about various defects so that, over time, it can get \",/*#__PURE__*/e(\"em\",{children:\"even better\"}),\" at its job.\\xa0\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[\"Moreover, because computer vision systems are trained on \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/best-free-datasets-for-machine-learning\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"thousands of datasets\"})}),\", they can override AOI shortcomings, including image quality issues and complicated surface textures to arrive at a precise assessment.\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[\"Using V7\u2019s software, you can train \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/object-detection-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"object detection,\"})}),\" \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/instance-segmentation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"instance segmentation\"})}),\" and\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/image-classification-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" image classification\"})}),\" models to spot defects and anomalies.\"]}),/*#__PURE__*/e(\"p\",{children:\"The more data you feed into the system, the easier it will be for the system to learn more about different types of defects.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"This allows it to make more accurate predictions on the future quality of a material or product, thus allowing your company to reach an error-free production.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"Naturally, there are still challenges involved. These include a lack of \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/quality-training-data-for-machine-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"training data\"})}),\", poor quality images/videos, as well as initial setup costs.\\xa0\"]}),/*#__PURE__*/e(\"h2\",{children:\"Quality assurance\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://asq.org/quality-resources/cost-of-quality\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"A report\"})}),\" showed that multiple organisations are struggling with quality assurance.\"]}),/*#__PURE__*/t(\"p\",{children:[\"And the problem is that quality-related costs are putting a \",/*#__PURE__*/e(\"em\",{children:\"huge\"}),\" dent into sales revenue (often as much as 20%, but sometimes as high as 40%).\"]}),/*#__PURE__*/e(\"p\",{children:\"These are staggering numbers. However, what we can deduce from this is that if companies were able to improve quality assurance, profits would soar.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Let\u2019s take an example of what we mean. Fast-moving consumer goods companies (FMGC) have long had a mutual problem: That of printed labels that are of such a poor quality that, when the code is applied to a wet label, the whole production line is brought to a standstill.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://connected.oalgroup.com/april-eye\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Computer vision solutions like APRIL Eye\"})}),\" are rectifying these issues, using image classification and object detection algorithms trained on super massive datasets to verify date and label codes at speeds of 1000+ packs per minute.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"Challenges like font distortion, missing text and varying fonts are overcome, and the production line isn\u2019t brought to a standstill.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Indeed, computer vision is playing a key role in the overall quality assurance processes in the manufacturing sector. Industries that are benefiting from its role in production process automation include electronics, automotive, general-purpose manufacturing and many, many more.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"For instance, the automotive industry benefits from paint surface inspection, foundry engine block inspection and press shop inspection. Computer vision systems are able to spot cracks, dents, scratches and other anomalies.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Want to learn more?\\xa0Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/computer-vision-applications\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"27+ Most Popular Computer Vision Applications and Use Cases\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"Meanwhile, in the electronics industry, the same systems can detect defective components, defective gluing and missing pieces, while in the general-purpose manufacturing industry, it can help with surface inspection, fabric inspection and packaging inspection.\"}),/*#__PURE__*/e(\"h2\",{children:\"Product assembly\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Elon Musk has long been seen as a trailblazer\u2014a Herculean man of science who\u2019s constantly breaking new ground.\"}),/*#__PURE__*/t(\"p\",{children:[\"And the ground he breaks isn\u2019t always as extravagant as sending rockets to Mars\u2014it\u2019s equally as grounded as improving Tesla\u2019s production lines, which are now\",/*#__PURE__*/e(a,{href:\"https://www.torquenews.com/11826/elon-musk-says-tesla-s-production-lines-already-over-75-percent-automated\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" over 75% automated\"})}),\".\"]}),/*#__PURE__*/e(\"p\",{children:\"Why does this matter?\"}),/*#__PURE__*/e(\"p\",{children:\"It matters because manufacturers\u2014as part of the industry 4.0 evolution\u2014are in general embracing automated product assembly processes.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Computer vision is used by multiple manufacturers to help improve their product assembly process. For example, using a computer vision inspection system to build 3D modelling designs, manufacturers are now able to streamline specific tasks that human workers have traditionally struggled with.\"}),/*#__PURE__*/e(\"p\",{children:\"Computer vision also assists operators with Standard Operating Procedures when the operators have to switch products numerous times in one day. This allows for more efficient processes. Moreover, it provides the workers with instructions to help them complete each step correctly.\"}),/*#__PURE__*/e(\"p\",{children:\"Managers are also informed each time there\u2019s a malfunction or other type of problem that needs to be rectified ASAP. To help with this, CV-powered cameras are installed, which feed images into an AI algorithm, which in turn scans the images for faults. When an issue is flagged by the algorithm, the manager is instantly notified and can then take action.\"}),/*#__PURE__*/t(\"p\",{children:[\"In a similar vein, object detection and\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/object-tracking-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" object tracking\"})}),\" are used to help manufacturers spot anomalies on the assembly line. Such anomalies might include cracks, scratches and other defects.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"And while robotic arms have been used in the product assembly process for a few years now, computer vision is able to improve their precision further by guiding and monitoring their arms.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Ultimately, improving product assembly processes via computer vision lowers the cost of production in the manufacturing industry by completing assembly processes with less error.\\xa0\"}),/*#__PURE__*/e(\"img\",{alt:\"Wine bottle counting using object detection\",className:\"framer-image\",src:\"https://framerusercontent.com/images/76SDMUHsxJ6wTyDGRZv8gkUprNM.png\",srcSet:\"https://framerusercontent.com/images/76SDMUHsxJ6wTyDGRZv8gkUprNM.png?scale-down-to=512 512w,https://framerusercontent.com/images/76SDMUHsxJ6wTyDGRZv8gkUprNM.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/76SDMUHsxJ6wTyDGRZv8gkUprNM.png 1984w\"}),/*#__PURE__*/e(\"h2\",{children:\"PPE detection\"}),/*#__PURE__*/t(\"p\",{children:[\"According to\",/*#__PURE__*/e(a,{href:\"https://www.ehstoday.com/ppe/hand-protection/article/21904489/workers-are-risking-injury-by-not-wearing-safety-equipment\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" NIOSH\"})}),\", more than 2,000 work-related injuries occur each day in American workplaces, with 80% of people who were at the American Society of Safety Engineers conference claiming to have seen workers operating without safety equipment (PPE).\"]}),/*#__PURE__*/t(\"p\",{children:[\"Moreover, 30% said they had seen workers operating without safety equipment on \",/*#__PURE__*/e(\"em\",{children:\"multiple \"}),\"occasions.\"]}),/*#__PURE__*/e(\"p\",{children:\"Naturally, those 2,000 work-related injuries can be massively reduced and even prevented altogether through the complete use of PPE.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The main problem here is that it\u2019s almost impossible for a company to monitor their workers all day long for the use of PPE.\"}),/*#__PURE__*/e(\"p\",{children:\"This is where AI comes in.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Computer vision-powered cameras are able to detect the likes of safety glasses, joint protectors, gloves, ear protectors, welding masks and goggles, high-vis jackets, face masks and hard hats. They can spot whenever a worker is wearing any or all of the above\u2014and whenever a worker who should be wearing any or all of the above has omitted an item or two (or three).\\xa0\"}),/*#__PURE__*/e(\"img\",{alt:\"PPE worker detection in a factory using computer vision\",className:\"framer-image\",src:\"https://framerusercontent.com/images/2jvN5ENY7lMCCOHpefycTLtOw.png\",srcSet:\"https://framerusercontent.com/images/2jvN5ENY7lMCCOHpefycTLtOw.png?scale-down-to=512 512w,https://framerusercontent.com/images/2jvN5ENY7lMCCOHpefycTLtOw.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/2jvN5ENY7lMCCOHpefycTLtOw.png 1386w\"}),/*#__PURE__*/e(\"p\",{children:\"At this point, we have to ask how effective computer vision is at spotting PPE.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"A\",/*#__PURE__*/e(a,{href:\"https://www.researchgate.net/publication/347857595_A_Real-Time_Computer_Vision_System_for_Workers'_PPE_and_Posture_Detection_in_Actual_Construction_Site_Environment\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" study\"})}),\" provides us with some answers, describing as it does real-time computer vision systems implemented at a construction site that is trained for PPE and posture detection.\"]}),/*#__PURE__*/t(\"p\",{children:[\"To construct the system, researchers amassed a huge dataset of 90+ videos using cameras installed onsite, before\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-annotation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" annotating the data\"})}),\" and training an object detection model.\"]}),/*#__PURE__*/e(\"p\",{children:\"The result was high-level stuff.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Recall and identification ratios were over 95% and 83%, while the classification of postures in both validation and model testing were 64% and 72%.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Looking to get hands on experience with labeling data? Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-labeling-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"What is Data Labeling and How to Do It Efficiently [Tutorial].\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"How is computer vision able to detect PPE?\"}),/*#__PURE__*/t(\"p\",{children:[\"It collects thousands of images from video recordings of multiple construction sites\u2014as many as 2,509 images according to one\",/*#__PURE__*/e(a,{href:\"https://www.frontiersin.org/articles/10.3389/fbuil.2020.00136/full\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" paper\"})}),\"\u2014before using deep learning to train the model.\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/deep-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Deep learning\"})}),\" is essential because without it, training object detection algorithms to process huge swathes of data is impossible. And without these huge swathes of data, the computer vision system isn\u2019t able to correctly differentiate objects, as well as contextualise them.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"The model used in the paper went on to achieve a 0.96 F1 score, while recall and precision rate averaged out at 96%.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"Ultimately, using computer vision for PPE detection in the manufacturing industry helps to reduce workplace accidents while saving a company money, and it also lowers insurance premiums \",/*#__PURE__*/e(\"em\",{children:\"and\"}),\" it can promote a better working culture.\\xa0\"]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Read \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-insurance\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"6 Viable AI Use Cases in Insurance.\"})})]})}),/*#__PURE__*/t(\"p\",{children:[\"Moreover, the process for adding a computer system for the purpose of PPE detection is far from challenging. Companies can use CCTV, surveillance cameras and others to collect the data, before using an\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/image-annotation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" image annotation\"})}),\" tool to label PPE equipment.\"]}),/*#__PURE__*/e(\"p\",{children:\"Then, the object detection model can be trained and applied to the company\u2019s computer vision system so that PPE is detected in real time.\"}),/*#__PURE__*/e(\"div\",{className:\"framer-text-module\",style:{\"--aspect-ratio\":\"560 / 315\",aspectRatio:\"560 / 315\",height:\"auto\",width:\"100%\"},children:/*#__PURE__*/e(n,{componentIdentifier:\"module:NEd4VmDdsxM3StIUbddO/1de6WpgIbCrKkRcPfQcW/YouTube.js:Youtube\",children:t=>/*#__PURE__*/e(r,{...t,play:\"Off\",shouldMute:!0,thumbnail:\"Medium Quality\",url:\"https://www.youtube.com/watch?v=0yM1MdfOiyE&feature=emb_title\"})})}),/*#__PURE__*/e(\"h2\",{children:\"Reading text and barcodes\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ocr-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Optical character recognition\"})}),\" detects and reads images\u2014printed, pre-printed and stamped\u2014via computer vision.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"OCR is able to easily decipher a text\u2014including all its different languages and fonts and styles\u2014and turn it into something meaningful, while at the same time digitalising it. This allows business faster access to actionable data.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"How does this help the manufacturing industry in particular?\"}),/*#__PURE__*/t(\"p\",{children:[\"Organisations typically experience a huge influx of incoming documents. OCR is able to help ease the burden, speed up operations and reduce human error by extracting data from \",/*#__PURE__*/e(\"em\",{children:\"all\"}),\" incoming documents before turning the data into something that is business-ready, and which can be indexed according to their titles, contents and keywords, before being actioned on.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"The usual steps needed for manual form processing are either reduced or eliminated altogether, which at the same time minimises\u2014or altogether eradicates\u2014human error. This is because OCR is able to identify data directly from scanned/printed images, thereby reducing data entry time.\\xa0\"}),/*#__PURE__*/e(\"img\",{alt:\"OCR performed on the inventory's labels using V7 Text Scanner\",className:\"framer-image\",src:\"https://framerusercontent.com/images/vGnJNp0mvT42B7OoARD93hdrpVo.png\",srcSet:\"https://framerusercontent.com/images/vGnJNp0mvT42B7OoARD93hdrpVo.png?scale-down-to=512 512w,https://framerusercontent.com/images/vGnJNp0mvT42B7OoARD93hdrpVo.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/vGnJNp0mvT42B7OoARD93hdrpVo.png 1110w\"}),/*#__PURE__*/e(\"p\",{children:\"ORC can carry out a number of tasks:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Expiration date verification\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Label placement\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Label verification\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Shipping data management\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Customer credits\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Expedited product returns\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Lot code and batch verification\\xa0\"})})]}),/*#__PURE__*/e(\"p\",{children:\"For example, you can use V7\u2019s public Text Scanner model for your OCR tasks:\"}),/*#__PURE__*/e(\"div\",{className:\"framer-text-module\",style:{\"--aspect-ratio\":\"560 / 315\",aspectRatio:\"560 / 315\",height:\"auto\",width:\"100%\"},children:/*#__PURE__*/e(n,{componentIdentifier:\"module:NEd4VmDdsxM3StIUbddO/1de6WpgIbCrKkRcPfQcW/YouTube.js:Youtube\",children:t=>/*#__PURE__*/e(r,{...t,play:\"Off\",shouldMute:!0,thumbnail:\"Medium Quality\",url:\"https://www.youtube.com/watch?v=Di6tcWoz_es\"})})}),/*#__PURE__*/e(\"p\",{children:\"Our Text Scanner works on all texts, including text that is:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Rotated\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Diagonally slanted\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Curved\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Extremely low resolution\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"In any language\\xa0\"})})]}),/*#__PURE__*/e(\"p\",{children:\"It also works on the following alphabets:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Latin\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Cyrillic\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Chinese simplified (Mandarin)\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Japanese\\xa0\"})})]}),/*#__PURE__*/e(\"p\",{children:\"Like all computer vision techniques, OCR isn\u2019t yet perfect.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"If there are poor lighting conditions or blurring to the text/image, OCR\u2019s capabilities \",/*#__PURE__*/e(\"em\",{children:\"could\"}),\" be lessened. However, there are already solutions in place that ensure OCR can overcome its challenges, while its deep learning processes ensure the system is able to achieve familiarity with printed texts super fast.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"It\u2019s also worth mentioning that numerous manufacturing companies have already adopted OCR.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"Indeed, the OCR market is expanding at a huge rate. According to\",/*#__PURE__*/e(a,{href:\"https://www.grandviewresearch.com/industry-analysis/optical-character-recognition-market\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" reports\"})}),\", its market size was valued at $7,460,000,000 in 2020, and is expected to achieve an annual growth rate of 16.7% within 7 years from now (2021).\\xa0\"]})]});export const richText6=/*#__PURE__*/t(o.Fragment,{children:[/*#__PURE__*/e(\"h2\",{children:\"Inventory Management\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Locating stock in a large warehouse isn\u2019t easy\u2014in fact, it\u2019s super challenging.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"Indeed, monitoring warehouse inventory on the whole is tricky to do with accuracy and efficiency. The aim is to monitor it with as much accuracy as possible, while eliminating allor, at least, \",/*#__PURE__*/e(\"em\",{children:\"most\"}),\" errors.\"]}),/*#__PURE__*/e(\"p\",{children:\"But with so many tasks to complete, including inventory audits, tagging and labeling, avoiding the kind of errors that can have a detrimental effect on the whole supply chain is far from easy.\"}),/*#__PURE__*/e(\"p\",{children:\"Unless businesses adopt computer vision systems, that is.\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Make sure to read \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/bounding-box-annotation-tool-features\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"9 Essential Features for a Bounding Box Annotation Tool \"})}),\"before choosing a platform for training object detection models.\"]})}),/*#__PURE__*/e(\"p\",{children:\"Computer vision is now used by manufacturing firms to:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Count stock\\xa0\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Take care of warehouse inventory status\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Instantly raise awareness to the manager(s) whenever material that is needed for manufacturing purposes is running out\\xa0\"})})]}),/*#__PURE__*/e(\"p\",{children:\"Traditionally, teams would track their inventory by walking around the warehouse with a pen and taking notes. This was time-consuming and subject to human error.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"Worse still, it means that tasks which could in \",/*#__PURE__*/e(\"em\",{children:\"theory\"}),\" be automated were being carried out by staff who could serve a more productive purpose elsewhere.\"]}),/*#__PURE__*/e(\"p\",{children:\"Computer vision automates the inventory management process by using techniques like object detection to track stock in real-time. It can locate empty containers, and ensure that restocking is fully optimised.\\xa0\"}),/*#__PURE__*/e(\"img\",{alt:\"Inventory management performed using computer vision\",className:\"framer-image\",src:\"https://framerusercontent.com/images/zFtUdfV5lBDWlvVX8P4pwHI64Y.jpg\",srcSet:\"https://framerusercontent.com/images/zFtUdfV5lBDWlvVX8P4pwHI64Y.jpg?scale-down-to=512 512w,https://framerusercontent.com/images/zFtUdfV5lBDWlvVX8P4pwHI64Y.jpg?scale-down-to=1024 1024w,https://framerusercontent.com/images/zFtUdfV5lBDWlvVX8P4pwHI64Y.jpg?scale-down-to=2048 2048w,https://framerusercontent.com/images/zFtUdfV5lBDWlvVX8P4pwHI64Y.jpg 2374w\"}),/*#__PURE__*/t(\"p\",{children:[\"For instance, such a system can use an AI algorithm to recognise supplies \",/*#__PURE__*/e(\"em\",{children:\"and\"}),\" how many are available (or, indeed, not available). \"]}),/*#__PURE__*/e(\"p\",{children:\"By monitoring the supplies and materials, as well as their movement through the warehouse, computer vision cameras can quickly identify when there\u2019s an empty space on a shelf, as well as alert managers each time stock needs to be replenished ASAP.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Want to understand object detection better? Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/yolo-object-detection\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"YOLO: Real-Time Object Detection Explained\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"Computer vision is also replacing the spreadsheets and clipboards that have been so intrinsic to inventory counts over the years with a platform that now displays automatically the information required in real time.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"And because manufacturing companies have access to real time updates to their inventory, they will save huge swathes of time searching for products/supplies/materials.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"Then there is\",/*#__PURE__*/e(a,{href:\"https://www.fronetics.com/send-in-the-drones-how-pinc-amazon-have-optimized-inventory-management/\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" autonomous technology (drones)\"})}),\", which the likes of Amazon and PINC have already adopted for inventory management. By adopting them, Amazon was able to slash their operating costs by 20%, which helped them to improve their operating margins.\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[\"PINC, meanwhile, combines their drones with computer vision systems, cloud computing, RFIC sensors \",/*#__PURE__*/e(\"em\",{children:\"and \"}),\"AI to track and monitor their warehouse assets.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"What can drones do?\"}),/*#__PURE__*/e(\"p\",{children:\"They can perform an inventory scan 100x faster than the average human worker. Even better, their inventory accurate rate is almost at 100%, while warehouse incidents and accidents are greatly reduced\u2014or eliminated altogether.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Amazon has taken things further. \"}),/*#__PURE__*/e(\"p\",{children:\"The eCommerce giant has also been working with AI-driven Kiva robots, which work on the factory floor, moving and stacking bins. These robots can also carry, transport and store merchandise that\u2019s as heavy as 3,000 lbs.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The benefit of using robots to complete these tasks lies with the customers: Because warehouses are able to transfer more goods, they\u2019re able to carry more inventory, which means customers will receive their orders faster.\\xa0\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Check out the\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-retail\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" 6 AI Applications That Are Shaping The Future of Retail.\"})})]})}),/*#__PURE__*/e(\"h2\",{children:\"Predictive Maintenance\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"How awesome would it be if you could detect a machine failure \u2026 \",/*#__PURE__*/e(\"em\",{children:\"before\"}),\" it happens? This would save so much money on repair costs.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"Detecting a machine failure before it happens requires three things:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The correct data\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The ability to analyse the data\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The proper corrective action\\xa0\"})})]}),/*#__PURE__*/e(\"p\",{children:\"With predictive maintenance, this is all now possible.\"}),/*#__PURE__*/e(\"p\",{children:\"What is predictive maintenance?\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"It uses IoT (Internet of Things) in conjunction with\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/machine-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" machine learning\"})}),\" to track machinery data, before collecting data points, finding signals\u2014and making the necessary adjustments so that components and assets don\u2019t break down.\\xa0\"]}),/*#__PURE__*/e(\"p\",{children:\"Data points are time stamped and help to provide an arsenal of machine performance metrics. Manufacturers can now train deep learning models so that they can find any potential defects in equipment and relay this information in real-time so that preventative action can be taken.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Potential problems might include leakage detection and fault diagnosis.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Not just that, but such solutions let managers monitor the current machine status of all their systems. By tracking data in real time like this, they can imitate real-time responses, as well as quickly understand the forecasted state of damage.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Systems that use computer vision tech can also improve their asset planning and maintenance scheduling.\"}),/*#__PURE__*/e(\"p\",{children:\"To use an example, data can tell a manager that if their team nudges their equipment\u2019s run rate up so as to boost production volumes, it could result in significant damage. The system may also find that graphic sleeves on a bottle of pop are being stretched, and that therefore production methods need to be changed so that the manufacturer remains within spec.\"}),/*#__PURE__*/e(\"p\",{children:\"To help with this, FANUC developed ZDT (Zero Down Time), a piece of software that gathers images from cameras, before sending them (and their accompanying metadata) to the cloud. After they\u2019ve been processed, they can spot any potential issues that may appear.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[\"All of this is important because\",/*#__PURE__*/e(a,{href:\"https://www.mckinsey.com/business-functions/operations/our-insights/manufacturing-analytics-unleashes-productivity-and-profitability\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" data\"})}),\" has shown that predictive maintenance tools are reducing downtime by as much as 50%, while at the same time boosting machine life by up to 40%.\\xa0\"]}),/*#__PURE__*/t(\"p\",{children:[\"Moreover, just a single minute of downtime in\u2014to use an example\u2014an automotive factory can take away\",/*#__PURE__*/e(a,{href:\"https://www.automate.org/industry-insights/remote-vision-system-monitoring-unleashes-predictive-maintenance-capabilities\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" $20,000 out of the profits\"})}),\" on high-profit cars, trucks and vans.\\xa0\"]}),/*#__PURE__*/e(\"h2\",{children:\"The\\xa0future of Artificial\\xa0Intelligence in Manufacturing\"}),/*#__PURE__*/e(\"p\",{children:\"Companies are already leveraging it to speed up their processes, improve safety, assist manual workers so that their skills can be used better elsewhere, and ultimately improve their bottom line.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The benefits of AI in manufacturing\u2014which already include reduced costs and saved time\u2014are set to continue, with companies able to spot problems before they arise, improve their product assembly line and use computer vision-based techniques to help scale their business.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Not started with computer vision yet?\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The good news is that we\u2019re still at the beginning\u2014and there\u2019s still time for you to introduce AI systems to your manufacturing processes.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"V7 arms you with the tools needed to integrate computer vision into your existing applications, and the good news is that you don\u2019t even need to be an expert.\\xa0\"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/get-started\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Contact V7 today\"})}),\" to start testing for free to see how it can fit into your manufacturing systems.\"]}),/*#__PURE__*/e(\"p\",{children:\"If you are interested to learn more about AI applications across other industries, check 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And we are happy to explain them in \",/*#__PURE__*/e(\"em\",{children:\"plain \"}),\"English.\"]}),/*#__PURE__*/e(\"p\",{children:\"Here\u2019s what we\u2019ll cover:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"What is Deep Learning?\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Deep Learning vs. Machine Learning\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"How does Deep Learning work?\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"How to create and train Deep Learning models\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Deep Learning limitations\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"4 Deep Learning applications\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Best Deep Learning resources\"})})]}),/*#__PURE__*/e(\"p\",{children:\"And if you want to skip the written guide, make sure to check out this detailed video introduction to Deep Learning.\"}),/*#__PURE__*/e(\"div\",{className:\"framer-text-module\",style:{\"--aspect-ratio\":\"560 / 315\",aspectRatio:\"560 / 315\",height:\"auto\",width:\"100%\"},children:/*#__PURE__*/e(n,{componentIdentifier:\"module:NEd4VmDdsxM3StIUbddO/1de6WpgIbCrKkRcPfQcW/YouTube.js:Youtube\",children:t=>/*#__PURE__*/e(r,{...t,play:\"Off\",shouldMute:!0,thumbnail:\"Medium Quality\",url:\"https://www.youtube.com/watch?v=5tvmMX8r_OM\"})})}),/*#__PURE__*/e(\"p\",{children:\"Now, let's break things down!\"})]});export const richText8=/*#__PURE__*/t(o.Fragment,{children:[/*#__PURE__*/e(\"h2\",{children:\"What is Deep Learning?\"}),/*#__PURE__*/t(\"p\",{children:[\"Deep Learning is a subset of \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/machine-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Machine Learning\"})}),\" that uses mathematical functions to map the input to the output. These functions can extract non-redundant information or patterns from the data, which enables them to form a relationship between the input and the output.\"]}),/*#__PURE__*/t(\"p\",{children:[\"This is known as \",/*#__PURE__*/e(\"strong\",{children:\"learning, \"}),\"and the process of learning is called \",/*#__PURE__*/e(\"strong\",{children:\"training\"}),\".\"]}),/*#__PURE__*/e(\"p\",{children:\"In traditional computer programming, input and a set of rules are combined together to get the desired output. In machine learning and deep learning, input and output are correlated to the rules. \"}),/*#__PURE__*/e(\"p\",{children:\"These rules\u2014when combined with new input\u2014yield desired results. \"}),/*#__PURE__*/e(\"img\",{alt:\"Classical programming vs machine learning\",className:\"framer-image\",src:\"https://framerusercontent.com/images/V0zL8nVSnsyTMjMBTmPWZVCM5pI.png\",srcSet:\"https://framerusercontent.com/images/V0zL8nVSnsyTMjMBTmPWZVCM5pI.png?scale-down-to=512 512w,https://framerusercontent.com/images/V0zL8nVSnsyTMjMBTmPWZVCM5pI.png 730w\"}),/*#__PURE__*/t(\"p\",{children:[\"Modern deep learning models use \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/neural-network-architectures-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"artificial neural networks\"})}),\" or simply neural networks to extract information. \"]}),/*#__PURE__*/t(\"p\",{children:[\"These neural networks are made up of a simple mathematical function that can be stacked on top of each other and arranged in the form of layers, giving them a sense of depth\",/*#__PURE__*/e(\"strong\",{children:\",\"}),\" hence the term \",/*#__PURE__*/e(\"em\",{children:\"Deep Learning. \"})]}),/*#__PURE__*/e(\"p\",{children:\"Deep learning can also be thought of as an approach to Artificial Intelligence, a smart combination of hardware and software to solve tasks requiring human intelligence.\"}),/*#__PURE__*/e(\"img\",{alt:\"Artificial Intelligence vs Machine Learning vs Deep Learning\",className:\"framer-image\",src:\"https://framerusercontent.com/images/fnk54mdpjaJ4gGkIJVForm8z76U.png\",srcSet:\"https://framerusercontent.com/images/fnk54mdpjaJ4gGkIJVForm8z76U.png?scale-down-to=512 512w,https://framerusercontent.com/images/fnk54mdpjaJ4gGkIJVForm8z76U.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/fnk54mdpjaJ4gGkIJVForm8z76U.png 1132w\"}),/*#__PURE__*/e(\"p\",{children:\"Deep Learning was first theorized in the 1980s, but it has only become useful recently because:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[\"It requires large amounts of \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/quality-training-data-for-machine-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"labeled data\"})})]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"It requires significant computational power (high performing GPUs)\"})})]}),/*#__PURE__*/e(\"p\",{children:\"If you are curious to learn more about the use of AI across various industries, check out:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-insurance\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"6 Viable AI Use Cases in Insurance\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-sports\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"7 Game-Changing AI Applications in the Sports 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Manufacturing\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-agriculture\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"8 Practical Applications of AI In Agriculture\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ai-in-healthcare\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"7 Life-Saving AI Use Cases in Healthcare\"})})})})]}),/*#__PURE__*/e(\"p\",{children:\"Next, we'll define the key elements that make up the Deep Learning algorithms.\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"If you are looking for a free image annotation tool, check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/cvat-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"The Complete Guide to CVAT\u2014Pros & Cons.\"})})]})}),/*#__PURE__*/e(\"h3\",{children:\"Neural Networks\"}),/*#__PURE__*/e(\"p\",{children:\"The neural network is the heart of deep learning models, and it was initially designed to mimic the working of the neurons in the human brain. \"}),/*#__PURE__*/e(\"p\",{children:\"Here are its components.\"}),/*#__PURE__*/e(\"img\",{alt:\"Neuron in Artificial Neural Network components\",className:\"framer-image\",src:\"https://framerusercontent.com/images/T95OcZmWTrct3g8ruBxIXRUWCHQ.png\",srcSet:\"https://framerusercontent.com/images/T95OcZmWTrct3g8ruBxIXRUWCHQ.png?scale-down-to=512 512w,https://framerusercontent.com/images/T95OcZmWTrct3g8ruBxIXRUWCHQ.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/T95OcZmWTrct3g8ruBxIXRUWCHQ.png 1240w\"}),/*#__PURE__*/e(\"p\",{children:\"The neuronal perception of deep learning is generally motivated by two main ideas: \"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"It is assumed that the human brain proves that intelligent behavior is possible, and\u2014by reverse engineering, it is possible to build an intelligent system\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Another perspective is that to understand the working of the human brain and the principles that underlie its intelligence is to build a mathematical model that could shed light on the fundamental scientific questions. \"})})]}),/*#__PURE__*/e(\"p\",{children:\"In essence, neural networks enable us to learn the structure of the data or information and help us to understand it by performing tasks such as clustering, classification, regression, or sample generation.\"}),/*#__PURE__*/e(\"h2\",{children:\"Deep Learning vs. Machine Learning\"}),/*#__PURE__*/e(\"p\",{children:\"Why is Deep Learning more powerful than traditional Machine Learning? \"}),/*#__PURE__*/e(\"p\",{children:\"Deep Learning can essentially do everything that machine learning does, but not the other way around. \"}),/*#__PURE__*/t(\"p\",{children:[\"For instance, machine learning is useful when the dataset is \",/*#__PURE__*/e(\"em\",{children:\"small\"}),\" and well-curated, which means that the data is carefully preprocessed. \"]}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/data-preprocessing-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Data preprocessing\"})}),\" requires human intervention. It also means that when the dataset is large and complex, machine learning algorithms will fail to extract information, and it will underfit. \"]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Looking for quality training data? Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/best-free-datasets-for-machine-learning\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"65+ Best Free Datasets for Machine Learning.\"})})]})}),/*#__PURE__*/t(\"p\",{children:[\"Generally, machine learning is alternatively termed \",/*#__PURE__*/e(\"em\",{children:\"shallow learning\"}),\" because it is very effective for smaller datasets. \"]}),/*#__PURE__*/e(\"p\",{children:\"Deep learning, on the other hand, is extremely powerful when the dataset is large. \"}),/*#__PURE__*/t(\"p\",{children:[\"It can learn any complex patterns from the data and can draw accurate conclusions on its own. In fact, deep learning is so powerful that it can even process unstructured data\u2014data that is not adequately arranged like text corpus, social media activity, etc.\",/*#__PURE__*/e(\"strong\",{children:\" \"})]}),/*#__PURE__*/e(\"p\",{children:\"Furthermore, it can also generate new data samples and find anomalies that machine learning algorithms and human eyes can miss. \"}),/*#__PURE__*/e(\"img\",{alt:\"The performance of deep learning vs. other learning algorithms\",className:\"framer-image\",src:\"https://framerusercontent.com/images/FVbQq01GRYMW1IfkIDnZ9Z44Ki8.jpeg\",srcSet:\"https://framerusercontent.com/images/FVbQq01GRYMW1IfkIDnZ9Z44Ki8.jpeg?scale-down-to=512 512w,https://framerusercontent.com/images/FVbQq01GRYMW1IfkIDnZ9Z44Ki8.jpeg?scale-down-to=1024 1024w,https://framerusercontent.com/images/FVbQq01GRYMW1IfkIDnZ9Z44Ki8.jpeg 1133w\"}),/*#__PURE__*/e(\"p\",{children:\"On the downside, deep learning is computationally expensive compared to machine learning, which also means that it requires a lot of time to process. \"}),/*#__PURE__*/t(\"p\",{children:[\"Deep Learning and Machine Learning are both capable of different types of learning: Supervised Learning (labeled data), Unsupervised Learning (unlabeled data), and \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/deep-reinforcement-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Reinforcement Learning\"})}),\". But their usefulness is usually determined by the size and complexity of the data. \"]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Learn more about \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/supervised-vs-unsupervised-learning\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Supervised vs. Unsupervised Learning.\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"To summarize:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Machine learning requires data preprocessing, which involves human intervention.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"The neural networks in deep learning are capable of extracting features; hence no human intervention is required. \"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Deep Learning can process unstructured data.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Deep Learning is usually based on representative learning i.e., finding and extracting vital information or patterns that represent the entire dataset. \\xa0 \"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Deep learning is computationally expensive and time-consuming. \"})})]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Check out \",/*#__PURE__*/e(a,{href:\"https://20+%20open%20source%20computer%20vision%20datasets/\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"20+ Open Source Computer Vision Datasets\"})}),\" to find quality data.\"]})}),/*#__PURE__*/e(\"h2\",{children:\"How does Deep Learning work?\"}),/*#__PURE__*/e(\"p\",{children:\"Now, let's dive in to learn how Deep Learning works.\"}),/*#__PURE__*/e(\"p\",{children:\"Deep Neural Networks have multiple layers of interconnected artificial neurons or nodes that are stacked together. Each of these nodes has a simple mathematical function\u2014usually a linear function that performs extraction and mapping of information.\"}),/*#__PURE__*/e(\"p\",{children:\"There are three layers to a deep neural network: the input layer, hidden layers, and the output layer.\"}),/*#__PURE__*/e(\"img\",{alt:\"Deep neural network architecture\",className:\"framer-image\",src:\"https://framerusercontent.com/images/1oemDyPGPWGzC8Cpq3EHxfwno.png\",srcSet:\"https://framerusercontent.com/images/1oemDyPGPWGzC8Cpq3EHxfwno.png?scale-down-to=512 512w,https://framerusercontent.com/images/1oemDyPGPWGzC8Cpq3EHxfwno.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/1oemDyPGPWGzC8Cpq3EHxfwno.png 1240w\"}),/*#__PURE__*/e(\"p\",{children:\"The data is fed into the input layer. \"}),/*#__PURE__*/e(\"p\",{children:\"Each node in the input layer ingests the data and passes it onto the next layer, i.e., the hidden layers. These hidden layers increasingly extract features from the given input layer and transform it using the linear function. \"}),/*#__PURE__*/e(\"p\",{children:\"These layers are called hidden layers because the parameters (weights and biases) in each node are unknown; these layers add random parameters to transform the data, each of which yields different output. \"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Read \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/neural-networks-activation-functions#3-activation-types\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"12 Types of Neural Network Activation Functions: How to Choose?\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"The output yielded from the hidden layers is then passed on to the final layer called the output layer, where depending upon the task, it classifies, predicts, or generates samples. \"}),/*#__PURE__*/t(\"p\",{children:[\"This process is called \",/*#__PURE__*/e(\"strong\",{children:\"forward propagation. \"})]}),/*#__PURE__*/e(\"img\",{alt:\"forward propagation in neural networks\",className:\"framer-image\",src:\"https://framerusercontent.com/images/4uGVcTMyRWssXe24Jbk0B8ApO0.jpg\",srcSet:\"https://framerusercontent.com/images/4uGVcTMyRWssXe24Jbk0B8ApO0.jpg?scale-down-to=512 512w,https://framerusercontent.com/images/4uGVcTMyRWssXe24Jbk0B8ApO0.jpg 800w\"}),/*#__PURE__*/t(\"p\",{children:[\"In another process called \",/*#__PURE__*/e(\"strong\",{children:\"backpropagation,\"}),\" an algorithm, like gradient descent, calculates errors by taking the difference between the predicted output and the original output. \"]}),/*#__PURE__*/e(\"p\",{children:\"This error is then adjusted by fine-tuning the weights and biases of the function by moving backward through the layers. \"}),/*#__PURE__*/e(\"p\",{children:\"Both, the process of forward propagation and backpropagation allows a neural network to reduce the error and achieve high accuracy in a particular task. With each iteration, the algorithm becomes gradually more accurate. \"}),/*#__PURE__*/e(\"h3\",{children:\"Types of neural networks\"}),/*#__PURE__*/e(\"p\",{children:\"There are several types of neural networks.\"}),/*#__PURE__*/e(\"h4\",{children:\"CNN\"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/convolutional-neural-networks-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"The Convolutional Neural Networks\"})}),\" or CNNs are primarily used for tasks related to computer vision or \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/image-processing-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"image processing\"})}),\". \"]}),/*#__PURE__*/t(\"p\",{children:[\"CNNs are extremely good in modeling spatial data such as 2D or 3D images and videos. They can extract features and patterns within an image, enabling tasks such as \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/image-classification-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"image classification\"})}),\" or \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/object-detection-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"object detection\"})}),\".\"]}),/*#__PURE__*/e(\"img\",{alt:\"Convolutional Neural Networks\",className:\"framer-image\",src:\"https://framerusercontent.com/images/Osa6EMdcOm7y4YviWKpVU6SpIeE.png\",srcSet:\"https://framerusercontent.com/images/Osa6EMdcOm7y4YviWKpVU6SpIeE.png?scale-down-to=1024 842w,https://framerusercontent.com/images/Osa6EMdcOm7y4YviWKpVU6SpIeE.png 1240w\"}),/*#__PURE__*/e(\"h4\",{children:\"RNN\"}),/*#__PURE__*/e(\"p\",{children:\"The Recurrent Neural Networks or RNN are primarily used to model sequential data, such as text, audio, or any type of data that represents sequence or time. They are often used in tasks related to natural language processing (NLP).\"}),/*#__PURE__*/e(\"img\",{alt:\"The Recurrent Neural Networks architecture\",className:\"framer-image\",src:\"https://framerusercontent.com/images/HcMiazYa8LZlIR3fUxNBLjICM.png\",srcSet:\"https://framerusercontent.com/images/HcMiazYa8LZlIR3fUxNBLjICM.png?scale-down-to=512 512w,https://framerusercontent.com/images/HcMiazYa8LZlIR3fUxNBLjICM.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/HcMiazYa8LZlIR3fUxNBLjICM.png 1240w\"}),/*#__PURE__*/e(\"h4\",{children:\"GAN\"}),/*#__PURE__*/e(\"p\",{children:\"Generative adversarial networks or GANs are frameworks that are used for the tasks related to unsupervised learning. This type of network essentially learns the structure of the data, and patterns in a way that it can be used to generate new examples, similar to that of the original dataset.\"}),/*#__PURE__*/e(\"img\",{alt:\"Generative Adversarial Metworks\",className:\"framer-image\",src:\"https://framerusercontent.com/images/h7i2zHbn18dRU1y98EhYTWMYzI.png\",srcSet:\"https://framerusercontent.com/images/h7i2zHbn18dRU1y98EhYTWMYzI.png?scale-down-to=1024 1004w,https://framerusercontent.com/images/h7i2zHbn18dRU1y98EhYTWMYzI.png 1240w\"}),/*#__PURE__*/e(\"h4\",{children:\"Transformers\"}),/*#__PURE__*/e(\"p\",{children:\"Transformers are the new class deep learning model that is used mostly for the tasks related to modeling sequential data, like that in NLP. It is much more powerful than RNNs and they are replacing them in every task. \"}),/*#__PURE__*/t(\"p\",{children:[\"Recently, transformers are also being applied in \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/computer-vision-applications\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"computer vision tasks\"})}),\" and they are proving to be quite effective than the traditional CNNs.\"]}),/*#__PURE__*/e(\"img\",{alt:\"Transformer Neural Networks\",className:\"framer-image\",src:\"https://framerusercontent.com/images/YWQv5kk7HfgmAHwK4czWzDn4E0A.png\",srcSet:\"https://framerusercontent.com/images/YWQv5kk7HfgmAHwK4czWzDn4E0A.png?scale-down-to=1024 637w,https://framerusercontent.com/images/YWQv5kk7HfgmAHwK4czWzDn4E0A.png 1240w\"})]});export const richText9=/*#__PURE__*/t(o.Fragment,{children:[/*#__PURE__*/e(\"h2\",{children:\"How to Create and Train Deep Learning Models\"}),/*#__PURE__*/e(\"p\",{children:\"In this section, we'll discuss two distinct strategies for training deep learning models.\"}),/*#__PURE__*/e(\"h3\",{children:\"Train from scratch\"}),/*#__PURE__*/e(\"p\",{children:\"To train a deep network from scratch, we need to have access to a large dataset, which you can find online. Once you have collected the data, you need to design a deep neural network that will extract and learn the features of the dataset. \"}),/*#__PURE__*/e(\"p\",{children:\"Designing a deep neural network can be a tedious task. \"}),/*#__PURE__*/e(\"p\",{children:\"In order to get started, you can make use of the V7. \"}),/*#__PURE__*/e(\"p\",{children:\"Here's a quick tutorial:\"}),/*#__PURE__*/t(\"p\",{children:[\"1. \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/get-started\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Sign up for the 14-day free trial \"})})]}),/*#__PURE__*/e(\"p\",{children:\"V7 now offers you three models that you can explore and train: Image Classification, Object Detection, Instance Segmentation.\"}),/*#__PURE__*/e(\"img\",{alt:\"V7 model training\",className:\"framer-image\",src:\"https://framerusercontent.com/images/z9PQ5gC4JlRdYWRyiimNlExNPCA.png\",srcSet:\"https://framerusercontent.com/images/z9PQ5gC4JlRdYWRyiimNlExNPCA.png?scale-down-to=512 512w,https://framerusercontent.com/images/z9PQ5gC4JlRdYWRyiimNlExNPCA.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/z9PQ5gC4JlRdYWRyiimNlExNPCA.png 1785w\"}),/*#__PURE__*/t(\"p\",{children:[\"V7 also comes with a public, in-built Text Scanner (OCR) model that you can use for document processing. It also provides an \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/go/document-automation\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"AI document automation platform\"})}),\" for extracting data from unstructured PDFs and other sources.\"]}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Learn more about \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/ocr-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Optical Character Recognition.\"})})]})}),/*#__PURE__*/e(\"p\",{children:\"2. To get started, go to the main dashboard of V7 and click on the \u2018Neural Networks\u2019 tab on the left.\"}),/*#__PURE__*/e(\"img\",{alt:\"V7 Neural Network Models dashboard\",className:\"framer-image\",src:\"https://framerusercontent.com/images/vgmAKqL9Eq1hD6TxtlGoXF3JKAw.png\",srcSet:\"https://framerusercontent.com/images/vgmAKqL9Eq1hD6TxtlGoXF3JKAw.png?scale-down-to=512 512w,https://framerusercontent.com/images/vgmAKqL9Eq1hD6TxtlGoXF3JKAw.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/vgmAKqL9Eq1hD6TxtlGoXF3JKAw.png 1600w\"}),/*#__PURE__*/e(\"p\",{children:\"3. Once you are in, you can then click on the +NEW MODEL button on the top right-hand corner, this will navigate you to the menu page, where you will find the three models:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Instance Segmentation\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Object Detection\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Classification\"})})]}),/*#__PURE__*/t(\"p\",{children:[\"Let us briefly walk you through the training of the \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/instance-segmentation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"instance segmentation model.\"})})]}),/*#__PURE__*/e(\"p\",{children:\"4. Select the Model card and click \u2018Continue\u2019 which will take you to the next page to select your dataset for training. \"}),/*#__PURE__*/e(\"img\",{alt:\"Picking the dataset for training \",className:\"framer-image\",src:\"https://framerusercontent.com/images/uew33smMWeTAfqVwZbDZd2ucc.png\",srcSet:\"https://framerusercontent.com/images/uew33smMWeTAfqVwZbDZd2ucc.png?scale-down-to=512 512w,https://framerusercontent.com/images/uew33smMWeTAfqVwZbDZd2ucc.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/uew33smMWeTAfqVwZbDZd2ucc.png 1655w\"}),/*#__PURE__*/t(\"p\",{children:['5. Once you have selected the dataset, click on \"Continue\". Next, you will see the breakdown of the number of images that will be used for ',/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/train-validation-test-set\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"training, validation, and testing.\"})})]}),/*#__PURE__*/e(\"img\",{alt:\"Training, validation, and test split in V7\",className:\"framer-image\",src:\"https://framerusercontent.com/images/eh7mMwwtxQwSNlwRMrbcStshzs.png\",srcSet:\"https://framerusercontent.com/images/eh7mMwwtxQwSNlwRMrbcStshzs.png?scale-down-to=512 512w,https://framerusercontent.com/images/eh7mMwwtxQwSNlwRMrbcStshzs.png?scale-down-to=1024 1024w,https://framerusercontent.com/images/eh7mMwwtxQwSNlwRMrbcStshzs.png 1700w\"}),/*#__PURE__*/e(\"p\",{children:\"6. Click on \u2018Start Training\u2019 which you will find at the bottom right of the dashboard. \"}),/*#__PURE__*/e(\"p\",{children:\"7. Once the training is completed, V7 will notify you via email that your model has finished training and is ready to use.\"}),/*#__PURE__*/e(\"h3\",{children:\"Transfer Learning\"}),/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/transfer-learning-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Transfer learning\"})}),\" is an approach\",/*#__PURE__*/e(\"em\",{children:\" w\"}),\"here you use an existing pre-trained model and fine-tune it with your desired dataset. This is the most common approach. \"]}),/*#__PURE__*/e(\"p\",{children:\"Networks such as AlexNet or GoogLeNet, VGG16, and VGG19 are some of the most common pre-trained networks. \"}),/*#__PURE__*/e(\"p\",{children:\"Transfer learning has advantages over training a model from scratch because:\"}),/*#__PURE__*/e(\"p\",{children:\"a) You don\u2019t need to design an entire architecture from scratch. \"}),/*#__PURE__*/e(\"p\",{children:\"b) The training time is shorter.\"}),/*#__PURE__*/e(\"p\",{children:\"c) You can train with less data.\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Check out \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/computer-vision-project-ideas\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"15+ Top Computer Vision Project Ideas for Beginners\"})}),\" to start building your own models.\"]})}),/*#__PURE__*/e(\"h2\",{children:\"Deep Learning Limitations\"}),/*#__PURE__*/e(\"p\",{children:\"We hope that this does not come as a surprise, but it's worth mentioning that Deep Learning, indeed, has several limitations. We've listed a few of them below.\"}),/*#__PURE__*/e(\"h3\",{children:\"Data availability\"}),/*#__PURE__*/e(\"p\",{children:\"Deep learning models require a lot of data to learn the representation, structure, distribution, and pattern of the data. \"}),/*#__PURE__*/e(\"p\",{children:\"If there isn't enough varied data available, then the model will not learn well and will lack generalization (it won't perform well on unseen data).\"}),/*#__PURE__*/e(\"p\",{children:\"The model can only generalize well if it is trained on large amounts of data.\"}),/*#__PURE__*/e(\"h3\",{children:\"The complexity of the model\"}),/*#__PURE__*/e(\"p\",{children:\"Designing a deep learning model is often a trial and error process.\"}),/*#__PURE__*/t(\"p\",{children:[\"A simple model is most likely to \",/*#__PURE__*/e(\"em\",{children:\"underfit\"}),\", i.e. not able to extract information from the training set, and a very complex model is most likely to \",/*#__PURE__*/e(\"em\",{children:\"overfit\"}),\", i.e., not able to generalize well on the test dataset. \"]}),/*#__PURE__*/e(\"p\",{children:\"Deep learning models will perform well when their complexity is appropriate to the complexity of the data. \"}),/*#__PURE__*/e(\"h3\",{children:\"Lacks global generalization\"}),/*#__PURE__*/e(\"p\",{children:\"A simple neural network can have thousands to tens of thousands of parameters. \"}),/*#__PURE__*/t(\"p\",{children:[\"The idea of global generalization is that all the parameters in the model should cohesively update themselves to reduce the \",/*#__PURE__*/e(\"strong\",{children:\"generalization error\"}),\" or \",/*#__PURE__*/e(\"strong\",{children:\"test error \"}),\"as much as possible. However, because of the complexity of the model, it is very difficult to achieve zero generalization error on the test set. \"]}),/*#__PURE__*/e(\"p\",{children:\"Hence, the deep learning model will always lack global generalization which can at times yield wrong results. \"}),/*#__PURE__*/e(\"h3\",{children:\"Incapable of Multitasking\"}),/*#__PURE__*/e(\"p\",{children:\"Deep neural networks are incapable of multitasking. \"}),/*#__PURE__*/e(\"p\",{children:\"These models can only perform targeted tasks, i.e., process data on which they are trained. For instance, a model trained on classifying cats and dogs will not classify men and women. \"}),/*#__PURE__*/e(\"p\",{children:\"Furthermore, applications that require reasoning or general intelligence are completely beyond what the current generation\u2019s deep learning techniques can do, even with large sets of data.\"}),/*#__PURE__*/e(\"h3\",{children:\"Hardware dependence\"}),/*#__PURE__*/e(\"p\",{children:\"As mentioned before, deep learning models are computationally expensive. \"}),/*#__PURE__*/e(\"p\",{children:\"These models are so complex that a normal CPU will not be able to withstand the computational complexity. However, multicore high-performing graphics processing units (GPUs) and tensor processing units (TPUs) are required to effectively train these models in a shorter time. \"}),/*#__PURE__*/e(\"p\",{children:\"Although these processors save time, they are expensive and use large amounts of energy.\"}),/*#__PURE__*/e(\"h2\",{children:\"4 Deep Learning Applications\"}),/*#__PURE__*/e(\"p\",{children:\"Now, let's have a closer look at the most important Deep Learning applications.\"}),/*#__PURE__*/e(\"img\",{alt:\"Applications of deep learning\",className:\"framer-image\",src:\"https://framerusercontent.com/images/jEOyWR6uKVrhiGmNsi5Kic18KbE.jpeg\",srcSet:\"https://framerusercontent.com/images/jEOyWR6uKVrhiGmNsi5Kic18KbE.jpeg?scale-down-to=512 512w,https://framerusercontent.com/images/jEOyWR6uKVrhiGmNsi5Kic18KbE.jpeg?scale-down-to=1024 1024w,https://framerusercontent.com/images/jEOyWR6uKVrhiGmNsi5Kic18KbE.jpeg 1133w\"}),/*#__PURE__*/e(\"p\",{children:\"Deep Learning finds applications in:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Speech recognition:\"}),\" Some of the familiar software like Apple\u2019s Siri, Google\u2019s Alexa, and Microsoft Cortana are based on deep neural networks. \"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Pattern recognition\"}),\": Pattern recognition is very useful in medical and life sciences. These algorithms can help radiologists to find tumor cells in the CT scans or even help them to understand the mechanism behind protein folding. Furthermore, other areas such as finance can also use pattern recognition systems to detect fraudulent transactions.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"NLP\"}),\": Natural language processing or NLP is one of the hot topics in deep learning these days. Modern architectures like the transformers have revolutionized and improved machine translation and language modeling. One of such models is GPT3 by Ope; it has almost reached general intelligence in all NLP tasks.\"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Recommender systems\"}),\": Recommender systems are on almost every social media platform these days from Instagram to YouTube and Netflix. These companies use a recommendation system to recommend shows, videos, posts, and stories based on users' activities. \"]})})]}),/*#__PURE__*/e(\"h3\",{children:\"Real-life Deep Learning use cases\"}),/*#__PURE__*/e(\"p\",{children:\"Finally, here are some of the real-life use cases of deep learning. \"}),/*#__PURE__*/e(\"h3\",{children:\"Healthcare\"}),/*#__PURE__*/e(\"ul\",{children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/medical-image-annotation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:/*#__PURE__*/e(\"strong\",{children:\"Medical image analysis\"})})}),/*#__PURE__*/e(\"strong\",{children:\": \"}),\"Medical images such as CT scans, MRI, and X-rays can sometimes be difficult to interpret; this mostly happens when the anomalies like the tumor get saturated in the background. \"]})})}),/*#__PURE__*/t(\"p\",{children:[\"Deep learning algorithms can help to find anomalies that are unseen to the naked eye. Algorithms like the Hierarchical Probabilistic U-Net by Google\u2019s DeepMind is one such example that is capable of finding tumor cells in\",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/healthcare-datasets-for-computer-vision\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\" medical images\"})}),\". Such algorithms are found to be a great tool for radiologists and doctors.\"]}),/*#__PURE__*/e(\"ul\",{children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Surgical robotics: \"}),\"There are times when a critical patient is unable to find a surgeon; in such dire and life-threatening conditions surgical robots can come to the rescue. Such robots have a superhuman ability to repeat exact motions like that of a trained surgeon. \"]})})}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/t(\"p\",{children:[\"Go to \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/dicom-annotation-tools\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!1,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Medical Image Annotation with V7\"})}),\" to learn more.\"]})}),/*#__PURE__*/e(\"h3\",{children:/*#__PURE__*/e(\"strong\",{children:\"Transportation\"})}),/*#__PURE__*/e(\"ul\",{children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Self-driving cars: \"}),\"Self-driving cars are becoming one of the trending topics in the world right now. Companies Tesla, Waymo, and others are pushing this trend of developing technology for safe driving. \"]})})}),/*#__PURE__*/e(\"p\",{children:\"All these companies use deep learning as their core algorithm; these models can consume a lot of data and enable these cars to navigate through roads while making correct decisions through analyzing the roads and vehicles around them. These cars are so advanced that they can even predict accidents. \"}),/*#__PURE__*/e(\"ul\",{children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Smart cities: \"}),\"Smart cities can manage their resources efficiently and manage traffic, public services, and disaster response. The way it works is that the input from different sensors from all over the city can be used to collect data and a deep learning system trained on that data can be used to predict different outputs based upon the scenario. \"]})})}),/*#__PURE__*/e(\"h3\",{children:\"Agriculture\"}),/*#__PURE__*/e(\"ul\",{children:/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Robot picking:\"}),\" Deep learning can be used to enable robots that can classify and pick crops. These robots can save time and increase the production rate as well. \"]})})}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Crop and soil monitoring: \"}),\"Deep learning model trained on the crop and soil condition data can be used to build a system that can effectively monitor crop and soil help estimate yield.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Livestock monitoring: \"}),\"Animals can move from one place to another, making them difficult to monitor. That\u2019s where \",/*#__PURE__*/e(a,{href:\"https://www.v7labs.com/blog/image-annotation-guide\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"image annotation for computer vision\"})}),\" comes in. Image annotation with deep learning can enable farmers to track the location, predict the livestock's food needs, and monitor the rest cycle to ensure that they are in good health. \"]})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[/*#__PURE__*/e(\"strong\",{children:\"Plant disease and pest detection: \"}),\"Another useful area for deep learning in agriculture is to classify plants suffering from the disease from healthy plants. This type of system can help farmers take proper treatment of the plant before they die. Furthermore, deep learning can also be used to detect pest infestation. \"]})})]}),/*#__PURE__*/e(\"h2\",{children:\"Best Deep Learning Resources\"}),/*#__PURE__*/e(\"p\",{children:\"Hungry for more? ;-) \"}),/*#__PURE__*/e(\"p\",{children:\"Check out our TOP 3 Deep Learning resources to learn more:\"}),/*#__PURE__*/t(\"ol\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.youtube.com/watch?v=0VH1Lim8gL8\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"https://www.youtube.com/watch?v=0VH1Lim8gL8\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.deeplearningbook.org/\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"https://www.deeplearningbook.org\"})})})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(a,{href:\"https://www.youtube.com/watch?v=v5cngxo4mIg&list=PLZbbT5o_s2xrfNyHZsM6ufI0iZENK9xgG\",motionChild:!0,nodeId:\"GdUtHI9Ua\",openInNewTab:!0,scopeId:\"contentManagement\",smoothScroll:!1,children:/*#__PURE__*/e(i.a,{children:\"Neural Network Programming Course\"})})})})]}),/*#__PURE__*/e(\"h2\",{children:\"Deep Learning: Key Takeaways\"}),/*#__PURE__*/e(\"p\",{children:\"We've learned today that Deep learning is a very versatile tool. \"}),/*#__PURE__*/e(\"p\",{children:\"Inspired by the biological brain deep learning has proven its usefulness in almost all areas of science and engineering. 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This correlation can be then used to cluster, predict, classify, and even generate new samples of data. \"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"One needs to train a deep learning model to make it learn and produce accurate results.\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/t(\"p\",{children:[\"The training process consists of two sub-processes called\",/*#__PURE__*/e(\"em\",{children:\" forward propagation\"}),\" and \",/*#__PURE__*/e(\"em\",{children:\"backward propagation\"}),\". 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