Hands-On Image Processing with Python

Convolutional layer

The main building block of CNN is the convolutional layer. The convolutional layer consists of a bunch of convolution filters (kernels), which we already discussed in detail in Chapter 2, Sampling, Fourier Transform, and Convolution. The convolution is applied on the input image using a convolution filter to produce a feature map. On the left side is the input to the convolutional layer; for example, the input image. On the right is the convolution filter, also called the kernel. As usual, the convolution operation is performed by sliding this filter over the input. At every location, the sum of element-wise matrix multiplication goes into the feature map. A convolutional layer is represented by its width, height (the ...