R Deep Learning Cookbook

How it works...

The dimensions and characteristics of an input image are shown in steps 1 and 2, respectively. Every input image is further processed in a convolution layer using a set of filters as defined in steps 4 and 5. The first convolution layer results in a set of 64 images (one for each set filter). In addition, the resolution of these images are also reduced to half (because of 2 x 2 max pooling); namely, from 32 x 32 pixels to 16 x 16 pixels.

The second convolution layer will input these 64 images and provide an output of new 64 images with further reduced resolutions. The updated resolution is now 8 x 8 pixels (again due to 2 x 2 max pooling). In the second convolution layer, a total of 64 x 64 = 4,096 filters are created, which ...