tph1r430nl驱动

根据提供的引用内容，tph1r430nl驱动并没有在所提到的引用中提及。无法提供关于tph1r430nl驱动的具体信息。请提供更多相关的引用内容以便我更好地回答您的问题。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *2* *3* [智能车竞赛技术报告 | 节能信标组 - 浙江大学 - 浙大三队](https://blog.csdn.net/zhuoqingjoking97298/article/details/120083269)[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: 100%"]
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相关问题

tph yolov5

TPH-YOLOv5是一种改进的YOLOv5模型，用于无人机捕获场景目标检测。它在YOLOv5基线代码的基础上进行了修改，专注于VisDrone2021数据集。该模型采用了Transformer编码块来替代YOLOv5原始版本中的卷积块和CSP瓶颈块。此外，TPH-YOLOv5还增加了一个用于微小物体检测的预测头，以处理目标的大尺度方差。这个预测头由低层高分辨率的特征图生成，对微小物体更加敏感，从而提高了对微小物体的检测性能。TPH-YOLOv5还集成了CBAM模块来帮助网络在大区域覆盖的图像中找到感兴趣的区域。通过这些改进，TPH-YOLOv5在VisDrone2021测试挑战数据集上达到了很好的性能，比DPNetV3的性能提高了1.81%。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* [TPH-YOLOv5用于无人机捕获场景目标检测](https://download.csdn.net/download/weixin_44911037/86823848)[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_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
- *2* [TPH-YOLOv5简述](https://blog.csdn.net/qq_40402444/article/details/121166319)[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_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
- *3* [TPH-YOLOv5](https://blog.csdn.net/m0_47405013/article/details/127071563)[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_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
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TPH-YOLOv5

TPH-YOLOv5是一种改进的目标检测模型，它在无人机捕获场景上展现出了良好的性能和可解释性。在VisDrone2021数据集上的实验结果显示，TPH-YOLOv5的平均精度(AP)为39.18%，比之前的SOTA方法(DPNetV3)提高了1.81%。在VisDrone Challenge 2021中，TPH-YOLOv5相比于YOLOv5提高了约7%的性能。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *3* [详细解读TPH-YOLOv5 | 让目标检测任务中的小目标无处遁形](https://blog.csdn.net/qq_42722197/article/details/125214116)[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^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
- *2* [TPH-YOLOv5: （中文翻译）](https://blog.csdn.net/weixin_42182534/article/details/123479460)[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^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
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