Essentially, the convolutional neural networks (CNNs) are artificial neural networks. In fact, just like the latter, CNNs are made up of neurons connected to each other by weighted branches (weight); the training parameters of the nets are once again the weight and the bias.
In CNNs, the connection pattern between neurons is inspired by the structure of the visual cortex in the animal world. The individual neurons present in this part of the brain (visual cortex) respond to certain stimuli in a narrow region of the observation, called the receptive field. The receptive fields of different neurons are partially overlapped so that they cover the entire field of view altogether. The response of a single neuron to stimuli ...
