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## (neural networks for object detection)
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* **Paper YOLOv7**: https://arxiv.org/abs/2207.02696
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* Paper **YOLOv7**: https://arxiv.org/abs/2207.02696
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* **source code YOLOv7 - Pytorch (use to reproduce results):** https://github.com/WongKinYiu/yolov7
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* source code YOLOv7 - Pytorch (use to reproduce results): https://github.com/WongKinYiu/yolov7
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----
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* **Paper YOLOv4**: https://arxiv.org/abs/2004.10934
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* Paper **YOLOv4**: https://arxiv.org/abs/2004.10934
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* **source code YOLOv4 - Darknet (use to reproduce results):** https://github.com/AlexeyAB/darknet
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* source code YOLOv4 - Darknet (use to reproduce results): https://github.com/AlexeyAB/darknet
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----
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* **Paper Scaled-YOLOv4 (CVPR 2021)**: https://openaccess.thecvf.com/content/CVPR2021/html/Wang_Scaled-YOLOv4_Scaling_Cross_Stage_Partial_Network_CVPR_2021_paper.html
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* Paper **Scaled-YOLOv4 (CVPR 2021)**: https://openaccess.thecvf.com/content/CVPR2021/html/Wang_Scaled-YOLOv4_Scaling_Cross_Stage_Partial_Network_CVPR_2021_paper.html
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* **source code Scaled-YOLOv4 - Pytorch (use to reproduce results):** https://github.com/WongKinYiu/ScaledYOLOv4
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* source code Scaled-YOLOv4 - Pytorch (use to reproduce results): https://github.com/WongKinYiu/ScaledYOLOv4
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@ -41,8 +41,7 @@ YOLOv7 surpasses all known object detectors in both speed and accuracy in the ra
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![image](https://user-images.githubusercontent.com/4096485/177674970-0c633f50-405d-4a20-a8d9-bd467d09d6ab.png)
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![more5](https://user-images.githubusercontent.com/4096485/179425274-f55a36d4-8450-4471-816b-8c105841effd.jpg)
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----
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