Building A Simple Convolution Layer From Scratch

A convolution layer provides a method of producing a feature map from a two-dimensional input. This is accomplished by running a filter over the input data. The filter is just a set of weights that must be trained to identify a feature in regions of the input data. These features can be things like edges, points, or more complex information. The filter will have dimensional constraints that indicate width and height, and it will scan over the input data.