🚀 *YOLOv5: The Controversial Yet Powerful Object Detection Model | Architecture Deep Dive* 🎯

In this video, we take a *deep dive into YOLOv5* , one of the most popular object detection models. We’ll cover:
✅ *Introduction to YOLOv5* – How it evolved from previous YOLO versions
✅ *The Controversy* – Why YOLOv5 doesn’t have an official research paper yet
✅ *Architecture Breakdown* – A layer-by-layer analysis of how YOLOv5 works
✅ *Comparison with YOLOv4* – Performance, speed, and accuracy

Despite the controversies, *YOLOv5 is widely used in real-world applications* , from autonomous driving to medical imaging. Watch till the end for a comprehensive breakdown!

💬 *What do you think about YOLOv5’s missing research paper? Does it impact its credibility? Let me know in the comments!*

Slides – https://drive.google.com/file/d/1Kg9R–mPPF1xgSYI3eQKknpYq61PeyCc/view?usp=share_link

🔗 *Resources & Code* : https://github.com/ultralytics/yolov5

📌 *Chapters* :
0:00 – Introduction
00:45 – Controversy: No official research paper?
04:30 – AGPL License
04:56 – YOLOv5 Architecture Overview
06:54 – Ultralytics Repo Capabilities
10:05 – Architecture Deepdive
11:00 – Backbone – Modified CSP-Darknet53
15:25 – SPPF Module
18:35 – CSP – Path Aggregation Network
24:30 – Detection Head
36:40 – Netron Visualization of Architecture
47:40 – Conclusion

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