深度学习之语义分割-FCN

We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, exceed the state-of-art in semantic segmentation
We define a novel architecture that combines semantic information from a deep, coarse layer with appearance information from a shallow, fine layer to produce accurate and detailed segmentation.

语义分割任务：

• semantic
• location：
  
  • 全局信息揭示种类：global information resolves what
  • 局部信息揭秘位置信息：local information resolves where

模型

• 说明：
  
  • 去掉基础模型VGG模型中的fc层，改为全卷积操作
  • 在特征层进行上采样，生成pixelwise prediction。
  • 通过’skip’连接，将deep/co