SnailTyan ● 首页 ● 分类 ● 归档 ● 标签 ● 关于 ResNet论文翻译——中文版 | | ResNet论文翻译——中文版 文章作者：Tyan 博客：noahsnail.com | CSDN | 简书 声明：作者翻译论文仅为学习，如有侵权请联系作者删除博文，谢谢！ 翻译论文汇总：https://github.com/SnailTyan/deep-learning-papers-translation Deep Residual Learning for Image Recognition Abstract Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We explicitly reformulate the layers as learning residual functions with reference to the layer inputs, instead of learning unreferenced functions. We provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth. On the ImageNet dataset we evaluate residual nets with a depth of up to 152 layers——8× deeper than VGG nets [40] but still having lower complexity. An ensemble of these resid
