Java Deep Learning Cookbook

Image preprocessing and the design of input layers

Normalization is a crucial preprocessing step for a CNN, just like for any feed forward networks. Image data is complex. Each image has several pixels of information. Also, each pixel is a source of information. We need to normalize this pixel value so that the neural network will not overfit/underfit while training. Convolution/subsampling layers also need to be specified while designing input layers for CNN. In this recipe, we will normalize and then design input layers for the CNN.