YOLOV7 improvement: replace WIOU to achieve lossless gains - Code World

YOLOV7 improvement: replace WIOU to achieve lossless gains

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Origin blog.csdn.net/m0_51530640/article/details/132474629

YOLOV7 improvement: replace WIOU to achieve lossless gains

YOLOV7 improvements: replaced by MPDIOU to achieve effective gains

yolov7 improvement series

YOLOv5 improvement series (11) - add loss function EIoU, AlphaIoU, SIoU, WIoU

Detailed explanation of YOLOv7 improvement

YOLOV5 improvements: replaced by MPDIOU to achieve effective gains

YOLOv5 Improvement Series (17)——Replacing MPDIoU of IoU (ELSEVIER 2023|Beyond WIoU, EIoU, etc.|Measured increase point)

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

YOLOV5/YOLOV7/YOLOV8 Improvement Column

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

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

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

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

YOLOv7 Improvement 22: Raising Point Artifact - Introducing Recursive Gated Convolution (gnConv)

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

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

[Practical Selection] Fruit Recognition System: Improvement of BoTNet-Transformer YOLOv7

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

YoloV8 improvement strategy: Based on hierarchical attention FasterViT, let YoloV8 achieve a leap in performance

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

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

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

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)

YOLOv5 improvement series (13) - replace the activation function of SiLU, ReLU, ELU, Hardswish, Mish, Softplus, AconC series, etc.

YOLOv5 Improvement Series (19) - Swin TransformerV1 to replace the backbone network (ViT model with smaller parameters)

YOLOv5 improvement series (18) - replace Neck's AFPN (new progressive feature pyramid | beyond PAFPN | measured increase point)

YOLOv5 Improvement Series (21) - RepViT to replace the backbone network (Tsinghua ICCV 2023|The latest open source mobile terminal ViT)

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