YOLOv9 Architecture Explained

Hey Deep Learning Lovers! A new YOLO version has come. Join me for the first ever complete breakdown of YOLOv9 architecture video.

YOLOv9 Explained? Yes, it is a super detailed YOLOv9 explanation video. I'll be your guide as we explore the key features behind YOLOv9 power. We'll also unravel the similarities to some other models.

Take a deep breath because we will deep dive (literally) into:
1. All YOLOv9 architecture components, such as: Conv block, RepConvN, RepNBottleneck, RepNCSP, REPNCSPELAN4, ADown, and SPPELAN.
2. The backbone, neck, and head, which is surprisingly, YOLOv9 has 6 head blocks now.
3. The Auxiliary which is one of the smart new features in YOLOv9

Join me for this fascinating journey, where we'll decode YOLOv9 architecture together! If you found this video helpful, click the thumbs up and share the video.

Chapters:
0:00 Introduction (YOLOv9 Components)
0:16 Convolution Block
1:28 RepConvN
2:35 RepNBottleneck
3:06 RepNCSP
3:46 RepNCSPELAN4
4:53 ADown
5:28 SPPELAN
6:32 The YOLOv9 OVERALL Architecture
6:59 Programmable Gradient Information (PGI)
7:49 Block Numbering
9:47 Determining Channel Output in RepNCSPELAN4
11:03 Neck Part (Upsample, Concat)
13:33 Auxiliary (CBLinear, CBFuse)

Btw, to be honest, YOLOv9 is very accurate in some cases, but YOLOv8 is better in some other cases. In my opinion, It is better if you learn both.

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Disclaimer: All information is based on our understanding of the paper and source code.
#yolov9 #yolov9architecture #objectdetection