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

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

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Origin blog.csdn.net/weixin_43694096/article/details/131726709

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 [SE] [CBAM] [ECA] [CA] attention mechanism in the C2F module | Attach a detailed structure diagram

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

yolov5 added CBAM, SE, CA, ECA attention mechanism, pure code (22.3.1 also updated)

YOLOv5-6.1 adds attention mechanism (SE, CBAM, ECA, CA)

Interpretation of Pytorch image processing attention mechanism SENet CBAM ECA module

Attention module SE, CBAM, ECA three code implementations

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

Attention mechanism - Convolutional Block Attention Module (CBAM)

Yolov5/Yolov7 improvement---attention mechanism: ICASSP2023 EMA is based on efficient multi-scale attention of cross-space learning, the effect is better than ECA, CBAM, CA | small target rises significantly

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

[Attention] CBAM mechanism CV in companion -BAM module

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

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

YOLOV7 adds CBAM attention mechanism in different positions

Detailed Interpretation of Vernacular (8) ----- CBAM: Convolutional Block Attention Module

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

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

YoloV8 improvement strategy: BAM bottleneck attention module | BAM detailed explanation and code comments | CBAM companion article | Effective points

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

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

CBAM: Convolutional Block Attention Module—— channel attention + spatial attention

ECA attention mechanism

[Attention] mechanism CV in the most simple and easy to implement SE module

Optimize and improve the receptive field attention convolution operation (RFAConv) of the YOLOv5 algorithm, and the effect is faster than CBAM and CA, etc.

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

Yolov8 improvement --- attention mechanism: CoordAttention, the effect spikes CBAM, SE

Yolov8 improves the CoTAttention attention mechanism, and the effect instantly kills CBAM and SE

Attention mechanism CBAM implementation

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