As you probably already know, a single-channel convolution works by sliding a 2D filter, usually smaller than the input matrix, across the height and width dimensions. For every sliding “window”, we then compute the weighted sum. The resulting output is a smaller 2D matrix. simple convolution Most of the time, however, we are dealing with tensors that have more than one channel (a colored image for example). Things get even more complicated when we want to have a different number of input and output channels.