If you've been following the latest news on self-driving cars (SDCs), you will have heard about convolutional neural networks (CNNs, or ConvNets). We use ConvNets to perform a multitude of perception tasks for SDCs. In this chapter, we will take a deeper look at this fascinating architecture and understand its importance. Specifically, you will learn how convolutional layers use cross-correlation, instead of general matrix multiplication, to tailor neural networks to the image input data. We'll also cover the advantages of these models over standard feed-forward neural networks.
ConvNets have neurons with learnable weights and biases. Similar to neural networks, each neuron in a ConvNet receives input, and then performs a dot product and follows non-linearity as well.
The pixels of raw images of the network...
