Using backpropagation, we are now able to train large networks automatically. This has led to the development of increasingly complex neural network architectures. One example is the convolutional neural network (CNN). There are mainly three types of layers in a CNN: the convolutional layer, the pooling layer, and the fully-connected layer. The fully-connected layer is identical to the standard neural network discussed previously. In the convolutional layer, weights are part of convolutional kernels. Convolution on a two-dimensional array of image pixels is defined as the following:
Where f(u, v) is the pixel ...
