yolov7与swim transformer相结合

将YOLOv7与Swin Transformer V2相结合可以进一步提升目标检测算法的性能。Swin Transformer V2是一种基于Transformer的新型模型结构，具有更好的扩展性和可解释性，并突破了传统CNN的性能瓶颈。通过在YOLOv7的backbone网络中集成Swin Transformer V2模块，形成了新的检测算法模型。这个新模型在多个数据集上进行测试，既保持了YOLOv7的高速和高精度特点，又进一步提升了性能。最近有一篇题为《Improving YOLOv5 Series by Combining Swin Transformer Structure》的论文获得了最佳论文奖项，该论文提出了一种新颖的算法YOLOv5 Swin Transformer，其在目标检测任务上表现出色。因此，将YOLOv7与Swin Transformer相结合可以提供更优秀的目标检测结果。<em>1</em><em>2</em><em>3</em>
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- *1* *2* [改进YOLOv7系列：YOLOv7与Swin Transformer V2的结合](https://blog.csdn.net/wellcoder/article/details/130935432)[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^v92^chatsearchT0_1"}} ] [.reference_item]
- *3* [YOLOv5与Swin Transformer相结合的分层视觉转换器——计算机视觉进阶](https://blog.csdn.net/wellcoder/article/details/131028235)[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^v92^chatsearchT0_1"}} ] [.reference_item]
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