Re-thinking Deep Residual Networks

本文是对ImageNet 2015的冠军ResNet(Deep Residual Networks)以及目前围绕ResNet这个工作研究者后续所发论文的总结，主要涉及到下面5篇论文。

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

因为出了ResNet，所以Google的researcher马上改造了Inception-v3的网络，引入了类似ResNet block的结构，实验证明，效果也确实变好了，文章就不过多解读了。

来源： http://freesouls.github.io/2016/03/30/rethinking-deep-residual-networks/

来自为知笔记(Wiz)