Scala for Machine Learning - Second Edition

Convolution neural networks

This section is provided as a brief introduction to convolution neural networks without Scala implementation. In a nutshell, a convolutional neural network is a feed-forward network with multiple hidden layers, some of them relying on convolution instead of matrix or tensor multiplication (w^T .x).

Up to this point, the layers of the perceptron were organized as a fully connected network. The number of synapses or weights increases significantly as the number and size of hidden layers increases. For instance, a network for a feature set with a dimension 6, three hidden layers of 64 nodes each, and 1 output value requires (7x64 + 2*65*64 + 65*1) = 8833 weights!

Applications such as image or character recognition require ...