A CNN consists of an input and an output layer; it also has various hidden layers. The following are the various hidden layers in a CNN:
- Convolution: Assume that we have an image represented as pixels, a convolution is something where we have a little matrix nearly always 3 x 3 in deep learning and multiply every element of the matrix by every element of 3 x 3 section of the image and then add them all together to get the result of that convolution at one point. The following diagram illustrates the process of convolution on a pixel:
Convolution application on an image
- Rectified Linear Unit (ReLU): A non-linear activation ...
