Math and Architectures of Deep Learning

10 Convolutions in neural networks

This chapter covers

• The graphical and algebraic view of neural networks
• Two-dimensional and three-dimensional convolution with custom weights
• Adding convolution layers to a neural network

Image analysis typically involves identifying local patterns. For instance, to do face recognition, we need to analyze local patterns of neighboring pixels corresponding to eyes, noses, and ears. The subject of the photograph may be standing on a beach in front of the ocean, but the big picture involving sand and water is irrelevant.

Convolution is a specialized operation that examines local patterns in an input signal. These operators are typically used to analyze images: that is, the input is a 2D array of pixels. To illustrate ...