Understanding CNNs

Now that we understand the high level concepts governing CNNs, let’s walk through the technical details of a CNN. First, we will discuss the convolution operation and introduce some terminology, such as filter size, stride, and padding. In brief, filter size refers to the window size of the convolution operation, stride refers to the distance between two movements of the convolution window, and padding refers to the way you handle the boundaries of the input. We will also discuss an operation that is known as deconvolution or transposed convolution. Then we will discuss the details of the pooling operation. Finally, we will discuss how to add fully connected layers, which produce the classification or regression output.

Convolution operation

In this section, we will discuss the convolution operation in detail. First, we will discuss the convolution operation without stride and padding, then we will describe the convolution operation with stride, and...