目标检测知识蒸馏损失函数

目标检测中的知识蒸馏损失函数是通过教师网络和学生网络之间的蒸馏损失函数以及学生网络和真实标签之间的softmax来定义的。根据引用中的描述，可以使用以下公式来计算损失：
loss = (0.3 * soft_loss + 0.7 * loss_c) + (0.5 * l2_loss + loss_l)
其中，soft_loss代表蒸馏损失函数，loss_c代表教师网络输出检测目标的概率和学生网络的交叉熵损失函数之间的差异，l2_loss代表学生网络预测的边界框与真实边界框之间的L2损失，loss_l代表学生网络预测的类别标签与真实类别标签之间的交叉熵损失。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* [目标检测知识蒸馏---以SSD为例【附代码】](https://blog.csdn.net/z240626191s/article/details/128759731)[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: 33.333333333333336%"]
- *2* [[深度学习入门]知识蒸馏](https://blog.csdn.net/Guycynnnnn/article/details/126557625)[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: 33.333333333333336%"]
- *3* [基于YOLOv4的目标检测知识蒸馏算法研究](https://blog.csdn.net/weixin_50094312/article/details/127519886)[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: 33.333333333333336%"]
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