3 Convolutional neural networks
This chapter covers
- Classifying images using MLP
- Working with the CNN architecture to classify images
- Understanding convolution on color images
Previously, we talked about artificial neural networks (ANNs), also known as multilayer perceptrons (MLPs), which are basically layers of neurons stacked on top of each other that have learnable weights and biases. Each neuron receives some inputs, which are multiplied by their weights, with nonlinearity applied via activation functions. In this chapter, we will talk about convolutional neural networks (CNNs), which are considered an evolution of the MLP architecture that performs a lot better with images.
The high-level layout of this chapter is as follows: