Improve YOLOv7 | Add [Triplet] [SpatialGroupEnhance] [NAM] [S2] attention mechanism to the ELAN module | Attached detailed structure diagram - Code World

Improve YOLOv7 | Add [Triplet] [SpatialGroupEnhance] [NAM] [S2] attention mechanism to the ELAN module | Attached detailed structure diagram

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Origin blog.csdn.net/weixin_43694096/article/details/133324575

Improve YOLOv7 | Add [Triplet] [SpatialGroupEnhance] [NAM] [S2] attention mechanism to the ELAN module | Attached detailed structure diagram

Improve YOLOv7 | Add [CA] [ECA] [CBAM] [SE] attention mechanism in ELAN module and ELAN-H module | Attach detailed structure diagram

Improve YOLOv8 | Plug and Play | Add [SimAM] [CoTAttention] [SKAttention] [Double Attention] attention mechanism in the C2F module | Attach a detailed structure diagram

Improve YOLOv8 | Plug and Play | Add [SE] [CBAM] [ECA] [CA] attention mechanism in the C2F module | Attach a detailed structure diagram

Yolov5/Yolov7 improvement --- attention mechanism: SimAM (no parameter Attention) and NAM (based on standardized attention module), the effect spikes CBAM, SE

Attention mechanism: based on Yolov8's Triplet attention module, plug and play, the effect is better than cbam and se, and the increase point is obvious

YOLOV7 improvement: Add RCS-OSA module to improve detection speed

YOLOV8 improvement: CVPR 2023 | Add EMA attention mechanism in different positions of C2f module, effectively increase points

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.71] attention mechanism Expectation-Maximization Attention (EMA module)

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.67] Add attention mechanism MHSA

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.72] attention mechanism Linear Context Transform Block (LCT module)

YOLOV7 adds CBAM attention mechanism in different positions

[Attention Mechanism Collection 2] BAM&SGE&DAN Detailed Explanation of Original Text, Structure and Source Code

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.70] NonDeepNe (ParNet module), a lightweight attention mechanism that does not increase network depth

Optimize and improve the YOLOv5 algorithm: add the SPD-Conv module to make small targets have nowhere to hide - (super detailed)

Yolov5/Yolov7 improvement --- attention mechanism: ShuffleAttention, ECA, EffectiveSE, SE

Yolov5/Yolov7 improvement --- attention mechanism: Polarized Self-Attention, the effect spikes CBAM, SE

Attention mechanism - Convolutional Block Attention Module (CBAM)

Add attention mechanism process + add expert network

Yolov7 paper study - innovation point analysis, network structure diagram

Detailed explanation of mask in attention mechanism

[7] YOLOv3 learn from scratch. Teach you to add Attention mechanism YOLOv3 model

YOLOv7-tiny network structure diagram and detailed notes of yaml file

Detailed interpretation of YOLOV7 (2) Interpretation of the paper

Translation: Detailed illustration of Transformer's multi-head self-attention mechanism Attention Is All You Need

[YOLOv7/YOLOv5 series improvement NO.53] Integrating the ECVBlock module in the CFPNet network to improve the detection ability of small targets

Essentials Attention mechanism summary attached: implementation English machine translation!

[Attention] CBAM mechanism CV in companion -BAM module

Detailed explanation of YOLOv7 network structure and training your own data

Detailed Attention Mechanism in Images (SEBlock | ECABlock | CBAM)

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