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        <title><![CDATA[Object Detection tutorials - Medium]]></title>
        <description><![CDATA[Learn object detection step-by-step with practical, code-driven tutorials. From YOLO and SSD to real-world datasets, video analytics, and model deployment, this publication helps you build production-ready detection projects with Python and modern CV tools. - Medium]]></description>
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            <title>Object Detection tutorials - Medium</title>
            <link>https://medium.com/object-detection-tutorials?source=rss----5aee5eaf3624---4</link>
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        <lastBuildDate>Tue, 10 Nov 2026 15:23:18 GMT</lastBuildDate>
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        <item>
            <title><![CDATA[Computer Vision in Python: How to Track Objects Without Deep Learning]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/computer-vision-in-python-how-to-track-objects-without-deep-learning-7b498b0e854d?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*_5cmhP6EDdsWXkfP_n6EhQ.jpeg" width="2752"></a></p><p class="medium-feed-snippet">Modern computer vision tutorials often push deep neural networks for simple motion tracking tasks. Spinning up heavyweight YOLO or&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/computer-vision-in-python-how-to-track-objects-without-deep-learning-7b498b0e854d?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/computer-vision-in-python-how-to-track-objects-without-deep-learning-7b498b0e854d?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[lucas-kanade]]></category>
            <category><![CDATA[computer-vision]]></category>
            <category><![CDATA[python]]></category>
            <category><![CDATA[object-detection]]></category>
            <category><![CDATA[object-tracking]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Mon, 09 Nov 2026 15:36:36 GMT</pubDate>
            <atom:updated>2026-11-09T15:36:38.352Z</atom:updated>
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        <item>
            <title><![CDATA[Build a Poker Hand Scanner: Card Recognition API Guide]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/build-a-poker-hand-scanner-card-recognition-api-guide-82eeae49a836?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*Zw1llIEfhi7uO0RO0QLxqQ.png" width="2752"></a></p><p class="medium-feed-snippet">Integrating a dedicated card recognition api into your workflow empowers software teams to inject production-ready computer vision into&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/build-a-poker-hand-scanner-card-recognition-api-guide-82eeae49a836?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/build-a-poker-hand-scanner-card-recognition-api-guide-82eeae49a836?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[detect-cards]]></category>
            <category><![CDATA[card-recognition]]></category>
            <category><![CDATA[object-detection]]></category>
            <category><![CDATA[card-api]]></category>
            <category><![CDATA[python]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Sat, 23 May 2026 14:52:54 GMT</pubDate>
            <atom:updated>2026-05-23T14:52:55.610Z</atom:updated>
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        <item>
            <title><![CDATA[Rethinking Computer Vision: Designing Custom Video Interfaces with YOLO11 and OpenCV]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/rethinking-computer-vision-designing-custom-video-interfaces-with-yolo11-and-opencv-160a1a4348d4?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*8CkDQmBFfQVGZgccr0MWxQ.png" width="2752"></a></p><p class="medium-feed-snippet">The world of computer vision moves incredibly fast, and the arrival of YOLO11 has raised the bar for real-time object detection efficiency&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/rethinking-computer-vision-designing-custom-video-interfaces-with-yolo11-and-opencv-160a1a4348d4?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/rethinking-computer-vision-designing-custom-video-interfaces-with-yolo11-and-opencv-160a1a4348d4?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[yolo]]></category>
            <category><![CDATA[annotations]]></category>
            <category><![CDATA[python]]></category>
            <category><![CDATA[object-detection]]></category>
            <category><![CDATA[yolov11]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Wed, 20 May 2026 15:49:17 GMT</pubDate>
            <atom:updated>2026-05-29T13:02:38.169Z</atom:updated>
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        <item>
            <title><![CDATA[Stateful Video Analytics: Building a Custom Line-Crossing Object Counter with YOLO11 and Python]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/stateful-video-analytics-building-a-custom-line-crossing-object-counter-with-yolo11-and-python-8ea57e837480?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*CfdKuGTpuCdONzlCiHN66w.png" width="2752"></a></p><p class="medium-feed-snippet">Getting Started with YOLO11 Object Counting Python for Real-World Analytics</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/stateful-video-analytics-building-a-custom-line-crossing-object-counter-with-yolo11-and-python-8ea57e837480?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/stateful-video-analytics-building-a-custom-line-crossing-object-counter-with-yolo11-and-python-8ea57e837480?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[multi-object-tracking]]></category>
            <category><![CDATA[yolov11]]></category>
            <category><![CDATA[object-counting]]></category>
            <category><![CDATA[object-tracking]]></category>
            <category><![CDATA[python]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Sun, 17 May 2026 16:28:09 GMT</pubDate>
            <atom:updated>2026-05-17T16:28:11.372Z</atom:updated>
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        <item>
            <title><![CDATA[Professional Vision Analytics: Mastering YOLO11 Tracking with PiP Overlays]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/professional-vision-analytics-mastering-yolo11-tracking-with-pip-overlays-4ae05e0405f4?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*012VMZHJv6i44socdYPH0g.png" width="2752"></a></p><p class="medium-feed-snippet">Modern computer vision is no longer just about drawing static boxes around objects; it is about extracting actionable, persistent&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/professional-vision-analytics-mastering-yolo11-tracking-with-pip-overlays-4ae05e0405f4?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/professional-vision-analytics-mastering-yolo11-tracking-with-pip-overlays-4ae05e0405f4?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[python]]></category>
            <category><![CDATA[object-tracking]]></category>
            <category><![CDATA[yolov11]]></category>
            <category><![CDATA[ultralytics]]></category>
            <category><![CDATA[object-detection]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Fri, 15 May 2026 05:58:35 GMT</pubDate>
            <atom:updated>2026-05-15T06:15:05.128Z</atom:updated>
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        <item>
            <title><![CDATA[AI in the Greenhouse: Mastering Tomato Disease Detection with PyTorch]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/ai-in-the-greenhouse-mastering-tomato-disease-detection-with-pytorch-08d76603bf5b?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*R-AtRsh6yi8GT9PL1k4thA.png" width="2752"></a></p><p class="medium-feed-snippet">Modern agriculture is undergoing a massive digital transformation, and at the center of this revolution is the ability to &#x201C;see&#x201D; what is&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/ai-in-the-greenhouse-mastering-tomato-disease-detection-with-pytorch-08d76603bf5b?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/ai-in-the-greenhouse-mastering-tomato-disease-detection-with-pytorch-08d76603bf5b?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[object-detection]]></category>
            <category><![CDATA[python]]></category>
            <category><![CDATA[plant-disease]]></category>
            <category><![CDATA[faster-r-cnn]]></category>
            <category><![CDATA[faster-rcnn]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Wed, 13 May 2026 18:23:40 GMT</pubDate>
            <atom:updated>2026-05-13T18:23:41.676Z</atom:updated>
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        <item>
            <title><![CDATA[Efficiency vs. Precision: A Python Deep Dive into Faster R-CNN and SSD PyTorch]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/efficiency-vs-precision-a-python-deep-dive-into-faster-r-cnn-and-ssd-pytorch-8067cdef2e92?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*h4hvJOodJRQ7UdG2uMsTxQ.png" width="2752"></a></p><p class="medium-feed-snippet">In the rapidly evolving landscape of artificial intelligence, selecting the optimal architecture for computer vision is rarely a simple&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/efficiency-vs-precision-a-python-deep-dive-into-faster-r-cnn-and-ssd-pytorch-8067cdef2e92?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/efficiency-vs-precision-a-python-deep-dive-into-faster-r-cnn-and-ssd-pytorch-8067cdef2e92?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[faster-r-cnn]]></category>
            <category><![CDATA[ssd]]></category>
            <category><![CDATA[ssdlite]]></category>
            <category><![CDATA[object-detection]]></category>
            <category><![CDATA[python]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Fri, 08 May 2026 15:00:12 GMT</pubDate>
            <atom:updated>2026-05-11T06:14:40.054Z</atom:updated>
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        <item>
            <title><![CDATA[How I Trained a Custom YOLO Model to Spot African Wildlife]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/how-i-trained-a-custom-yolo-model-to-spot-african-wildlife-9bc70106ab58?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*0bWHM3P4T2d48JMBGBaAJg.png" width="2752"></a></p><p class="medium-feed-snippet">Computer vision holds incredible potential when it comes to observing animals in their natural environments. This article provides a&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/how-i-trained-a-custom-yolo-model-to-spot-african-wildlife-9bc70106ab58?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/how-i-trained-a-custom-yolo-model-to-spot-african-wildlife-9bc70106ab58?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[yolo]]></category>
            <category><![CDATA[yolo2026]]></category>
            <category><![CDATA[yolov11]]></category>
            <category><![CDATA[python]]></category>
            <category><![CDATA[object-detection]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Fri, 01 May 2026 11:53:36 GMT</pubDate>
            <atom:updated>2026-05-08T11:43:27.802Z</atom:updated>
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        <item>
            <title><![CDATA[Training an AI to Identify 43 Military Aircraft]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/training-an-ai-to-identify-43-military-aircraft-6c04628e746e?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*BmfK-kWS_mdwHhkJ-20zDA.png" width="2752"></a></p><p class="medium-feed-snippet">Imagine trying to teach a machine to distinguish between the subtle silhouette of an F-22 Raptor and an F-35 Lightning II across thousands&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/training-an-ai-to-identify-43-military-aircraft-6c04628e746e?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/training-an-ai-to-identify-43-military-aircraft-6c04628e746e?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[yolov11]]></category>
            <category><![CDATA[open-image-dataset]]></category>
            <category><![CDATA[yolov11-tutorial-pytorch]]></category>
            <category><![CDATA[pytorch]]></category>
            <category><![CDATA[object-detection]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Mon, 27 Apr 2026 13:37:59 GMT</pubDate>
            <atom:updated>2026-04-27T13:38:01.228Z</atom:updated>
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        <item>
            <title><![CDATA[How to Fine-Tune YOLO-World for Vision Tasks | Underwater trash]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/object-detection-tutorials/how-to-fine-tune-yolo-world-for-vision-tasks-underwater-trash-b1b5af8362f8?source=rss----5aee5eaf3624---4"><img src="https://cdn-images-1.medium.com/max/2600/1*PWHHf7-mWlJXAoRA7lVu0Q.png" width="2752"></a></p><p class="medium-feed-snippet">The evolution of computer vision has reached a fascinating intersection where &#x201C;open-vocabulary&#x201D; models allow us to detect almost anything&#x2026;</p><p class="medium-feed-link"><a href="https://medium.com/object-detection-tutorials/how-to-fine-tune-yolo-world-for-vision-tasks-underwater-trash-b1b5af8362f8?source=rss----5aee5eaf3624---4">Continue reading on Object Detection tutorials »</a></p></div>]]></description>
            <link>https://medium.com/object-detection-tutorials/how-to-fine-tune-yolo-world-for-vision-tasks-underwater-trash-b1b5af8362f8?source=rss----5aee5eaf3624---4</link>
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            <category><![CDATA[object-detection]]></category>
            <category><![CDATA[fine-tuning]]></category>
            <category><![CDATA[yolo-world]]></category>
            <category><![CDATA[python]]></category>
            <category><![CDATA[underwater]]></category>
            <dc:creator><![CDATA[Eran Feit]]></dc:creator>
            <pubDate>Mon, 20 Apr 2026 13:24:03 GMT</pubDate>
            <atom:updated>2026-04-20T13:24:04.633Z</atom:updated>
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