ResNet解析：Deep Residual Learning for Image Recognition
Microsoft的ResNet赢得了ILSVRC 2015 和COCO 2015的冠军。 它是为了解决在深度神经网络中，随着深度的加深，training error会增大。 这显然不是因为overfitting，因为overfitting的表现是在train set上表现很好，test set上表现变差。 它的基本模块结构如下： 定义公式是： 这里，x，y分别代表每一层的输入与输出。代表残差，需
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相关文章
- 1. ResNet--Deep Residual Learning for Image Recognition
- 2. [ResNet]Deep Residual Learning for Image Recognition
- 3. ResNet —— Deep Residual Learning for Image Recognition
- 4. ResNet(deep residual learning for image recognition)
- 5. ResNet——Deep Residual Learning for Image Recognition
- 6. 【Deep Learning】ResNet解析：Deep Residual Learning for Image Recognition
- 7. Deep Residual Learning for Image Recognition（ResNet） 阅读
- 8. Deep Residual Learning for Image Recognition
- 9. Deep Residual Learning for Image Recognition （zh）
- 10. Deep Residual Learning For Image Recognition