repvgg yolov5

repvgg是一种轻量级的卷积神经网络结构，它可以用于改进YOLOv5等目标检测网络的性能。repvgg结构通过将常规卷积替换为由多个重复卷积组成的模块来减少参数量，从而实现了高效的计算和准确的检测结果。此外，repvgg结构还可以结合注意力机制来提升目标检测的性能。通过在YOLOv5中集成repvgg结构和注意力机制，可以实现更好的目标检测效果。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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- *1* *3* [【YOLOv7/YOLOv5系列改进NO.38】引入RepVGG模型结构](https://blog.csdn.net/m0_70388905/article/details/127532645)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
- *2* [改进yolov5(多检测头+注意力机制+repvgg结构)pytorch源码+项目说明.zip](https://download.csdn.net/download/DeepLearning_/87249653)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
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