YOLOV7改进-具有位置编码信息的Attention-based Intrascale Feature Interaction
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RTDETR改进-最新的FPN变种High-level Screening-feature Pyramid Networks,并对其进行二次创新
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YOLOV7改进-添加CoordConv
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YOLOV7改进-对小目标有利的Scale Sequence Feature Fusion
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YOLOV9改进-CVPR2023-FasterNet以及其FasterBlock、PConv的改进
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YOLOV7剪枝-ReXNet(CVPR2021)+VoVGSCSP+DyHead+解耦头
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YOLOV8改进-CVPR2024-StarNet超越CVPR2023-FasterNet(新SOTA)
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基于ultralytics的RT-DETR集成计算量更小的RT-DETR并转换预训练权重
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YOLOV7改进-针对小目标的NWD
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YOLOV7改进-对小目标有效的BiFormer注意力机制(附带在yolov7中简易添加注意力的详细教程)
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YOLOV5,V7-剪枝项目介绍
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YOLOV5改进-重参数化Transformer-RepViT
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YOLOV8改进模型轻量化示例：RepViT(CVPR2024)+RepNCSPELAN(YOLOV9)+LAMP
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YOLOV7改进-对小目标有提点的Omni-Dimensional Dynamic Convolution
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YOLOV7改进-Wise IoU
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全网最快!YOLOV7改进-利用华为2023最新GOLD-YOLO中的Gatherand-Distribute进行改进特征融合模块
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给YOLOV8换了个RT-DETR的TransformerDecoderHead后在VisDrone2019提升了4个点!
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YOLOV8、RTDETR改进项目介绍~(里面有较多二次创新、原创模块喔)
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YOLOV5改进-(CVPR2023)具有级联分组注意力的EfficientViT
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YOLOV8改进-又轻量又提点的SlimNeck
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YOLOV7改进-添加EIOU,SIOU,AlphaIOU,FocalEIOU.
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YoloV7-pyqt5 3.yolov7-pyqt5使用教程
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RTDETR改进-Parallel Atrous Convolution Attention Pyramid Network
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YOLOV5改进-对小目标有利的Scale Sequence Feature Fusion
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你知道目标检测检测中的mAP50中的50代表的是什么吗？
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YOLOV8改进-CVPR2022最佳论文Vision Transformer with Deformable Attention
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YOLOV7改进-Soft-NMS(支持多种IoU变种选择)
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YoloV7保姆级教学视频
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YOLOV7改进-加入最新的Shape-IoU
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YOLOV7改进-添加FasterNet中的PConv
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YOLOV7改进-CVPR2021-DiverseBranchBlock
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YOLOV8改进-添加基于注意力机制的目标检测头DyHead
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YOLOV5改进-对小目标有效的BiFormer注意力机制
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YOLOV5改进-具有轻量化效果的cross-scale feature-fusion module
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YOLOV8改进-CPCA注意力机制,EMASlideLoss,KernelWarehouse,Dynamic Snake Convolution,NWD
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YOLOV8改进-添加EIOU,SIOU,AlphaIOU,FocalEIOU.
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YOLOV8改进-使用最新的EMA注意力机制与C2f-Faster融合 C2f-Faster-EMA
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YOLOV7剪枝-嫌FasterNet还不够小?那就尝试FasterNet与剪枝结合!
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不想改YOLO?YOLO感觉不好发?要不来试试RT-DETR?
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YOLOV9改进-DySnakeConv动态蛇形卷积、针对长条形不规则物体！
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YOLOV8改进-Attentional Scale Sequence Fusion与Small Object Detection Head的融合