Build a Residual Module and a Residual Convolutional Network
As always, using Keras and Tensorflow!
In the last article, we learned about Residual Connections and their importance in neural networks to prevent gradient vanishing. In this article we we will learn how to build a Residual module and how to implement a full convolutional neural network with residual connections, as well as to compare the performance with a sequential convolutional neural network. Keep reading!
The first step in this article is to build a residual module. If haven't read my past articles on convolutional networks, I strongly recommend you do so, and get familiar with convolutional layers, batch normalization, and activation functions.