yolov7 mobileone

YOLOv7 MobileOne是基于YOLOv7算法改进的一种轻量高效的物体检测模型。研究人员通过引入MobileOne结构和苹果Backbone主干网络模型进行优化，提高了YOLOv7的性能和效率。MobileOne是一种超轻量型架构，由苹果公司提出并在iPhone 12上进行了优化。它在ImageNet数据集上取得了很好的速度和准确率表现。

此外，YOLOv7 MobileOne还兼容MobileOne官方的预训练权重，这样可以更方便地在YOLOv7项目中使用。 你可以在GitHub上找到相关的官方预训练权重文件。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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- *1* [YOLOv7_轻量高效MobileOne结构与苹果Backbone主干网络模型](https://blog.csdn.net/wellcoder/article/details/130995184)[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: 33.333333333333336%"]
- *2* [MobileOne实战：使用MobileOne实现图像分类任务.zip](https://download.csdn.net/download/hhhhhhhhhhwwwwwwwwww/87218460)[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: 33.333333333333336%"]
- *3* [【YOLOv7改进轻量化】第一章——引入轻量化骨干网络MobileOne](https://blog.csdn.net/weixin_44994302/article/details/128156130)[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: 33.333333333333336%"]
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