YOLOv7 algorithm reconstruction: personal self-improvement, as simple as YOLOv5, only 31 layers - Code World

YOLOv7 algorithm reconstruction: personal self-improvement, as simple as YOLOv5, only 31 layers

Enterprise 2023-06-19 17:35:14 views: null

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Origin blog.csdn.net/qq_44224801/article/details/130907083

YOLOv7 algorithm reconstruction: personal self-improvement, as simple as YOLOv5, only 31 layers

[YOLOv7/YOLOv5 series algorithm improvement NO.7] Loss function improvement

yolov3 yolov4 yolov5 yolov6 yolov7 yolov8 yolox Algorithm improvement, algorithm customization, algorithm guidance

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.71] attention mechanism Expectation-Maximization Attention (EMA module)

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

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.73] Adding asymptotic feature pyramid network (AFPN module)

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.85] Use TransformerDecoderHead in RT-DETR to improve yolov5

[YOLOv7/YOLOv5 series algorithm improvement NO.8] Non-maximum suppression NMS algorithm improvement Soft-nms

Video target detection yolo algorithm small model self-training model comparison (yolov5 yolov7 yolov8)

YOLOV5/YOLOV7/YOLOV8 Improvement Column

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement [NO.69] Improvement of small targets in remote sensing image target detection CATnet (ContextAggregation module)

[YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvement NO.65] CVPR 2023 | Tsinghua team's plug-and-play network architecture—Slide-Transformer

YOLOv7 Improvement: CVPR 2023 | SCConv: Plug-and-Play Convolution for Spatial and Channel Reconstruction

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

Gain point artifact: small target performance improvement based on Yolov5/Yolov7

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

yolov7 improvement series

Nanny level tutorial - YOLO series (YOLOv5/YOLOv7/YOLOv8) algorithm training data set

[YOLOv7/YOLOv5 series improvement NO.52] Integrating the C2f module in YOLOv8

Interpretation of Yolov5 algorithm

Target detection algorithm Yolov7

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.79] The improved loss function is VariFocal Loss

YOLOv8/YOLOv7/YOLOv5/YOLOv4/Faster-rcnn series algorithm improvements [NO.83] Change the backbone feature extraction network Backbone to RevCol

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

Detailed explanation of YOLOv7 improvement

Target detection algorithm (R-CNN, fast R-CNN, faster R-CNN, yolo, SSD, yoloV2, yoloV3, yoloV4, yoloV5, yoloV6, yoloV7)

Reconstrucción del algoritmo YOLOv7: superación personal, tan simple como YOLOv5, solo 31 capas

yolov5 pedestrian detection algorithm

Analysis of YOLOv5 algorithm for target detection

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