本文是對ImageNet 2015的冠軍ResNet(Deep Residual Networks)以及目前圍繞ResNet這個工作研究者後續所發論文的總結，主要涉及到下面5篇論文。
1. Link: Highway Networks:
Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber
2. Link: Deep Residual Learning for Image Recognition:
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
3. Link: Identity Mappings in Deep Residual Networks:
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
4. Link: ResNet in ResNet: Generalizing Residual Architectures:
Sasha Targ, Diogo Almeida, Kevin Lyman
5. Link: Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning:
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke
Highway Networks
Deep Residual Learning for Image Recognition
Identity Mappings in Deep Residual Networks
ResNet in ResNet: Generalizing Residual Architectures
Inception-v4, Inception-ResNet
因爲出了ResNet，所以Google的researcher馬上改造了Inception-v3的網絡，引入了類似ResNet block的結構，實驗證明，效果也確實變好了，文章就不過多解讀了。
本文標題:Re-thinking Deep Residual Networks
文章作者:Binbin Xu
發佈時間:2016年03月30日 - 19時21分
最後更新:2016年03月31日 - 15時18分
原始鏈接:http://freesouls.github.io/2016/03/30/rethinking-deep-residual-networks/
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