Understanding Convolution Neural Networks

Now 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 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 connect fully connected layers and the two-dimensional outputs produced by the convolution and pooling layers and how to use the output for classification or regression.

Convolution operation

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