YOLOV7 adds CBAM attention mechanism in different positions - Code World

YOLOV7 adds CBAM attention mechanism in different positions

Enterprise 2023-06-05 20:41:12 views: null

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Origin blog.csdn.net/m0_51530640/article/details/128760029

YOLOV7 adds CBAM attention mechanism in different positions

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

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

Attention mechanism CBAM implementation

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

YOLOV5 improvement: CVPR 2023 | Add EMA attention mechanism in different positions of C3 block, effectively increase points

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

CBAM attention mechanism - pytorch implementation

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

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

YOLOV5 adds attention mechanism, taking ECAttention as an example (series)

[Deep Learning Attention Mechanism Series] - CBAM Attention Mechanism (with pytorch implementation)

[Attention] CBAM mechanism CV in companion -BAM module

Attention mechanism CBAM code implementation (sequel)

Robot Grabbing Series - CBAM Attention Mechanism

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

YOLOv5 improvements | 2023 attention | EMAttention attention mechanism (with multiple positions that can be added)

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

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

[Selected] Highway Intelligent Inspection System: CBAM Spatial Attention Mechanism Improved YOLOv5

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

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

Interpretation of Pytorch image processing attention mechanism SENet CBAM ECA module

yolov7 adds mobileone

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)

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

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