Large-Margin Softmax Loss for Convolutional Neural Networks
Large-Margin Softmax Loss for Convolutional Neural Networks 在本文中，我们将软最大损耗定义为交叉熵损耗、软最大函数和最后一个完全连接层的组合（见图1）。在这种定义下，许多流行的CNN模型可以被视为卷积特征学习组件和softmax损失组件的组合，如图1所示。 尽管它的流行，当前的软最大损失并不明确鼓励类内的紧密性和类间的可分离性。 我们的主
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相关文章
- 1. Large-Margin Softmax Loss for Convolutional Neural Networks
- 2. softmax变种或增强1：Large-Margin Softmax Loss for Convolutional Neural Networks
- 3. 论文笔记 | Large-Margin Softmax Loss for Convolutional Neural Networks
- 4. Bag of Tricks for Convolutional Neural Networks
- 5. Convolutional Neural Networks: Application
- 6. CS231n Convolutional Neural Networks for Visual Recognition
- 7. Large-Margin Softmax Loss
- 8. Convolutional Neural Networks for Visual Recognition
- 9. 《Convolutional Neural Networks for Sentence Classification》
- 10. Recurrent Convolutional Neural Networks for Text Classification