A Quick Intro To Convolutions In CNNs

Disclaimer: This article requires a basic understanding of neural networks and how fully connected layers function. Convolutional neural networks (CNNs) are a type of network architecture that is commonly used in computer vision tasks. The convolutional layers provide several advantages over fully connected layers, which are commonly used in classical neural network architectures. The main functionality of the convolutional layers is to detect features inside the images while reducing the required computational power in comparison to fully connected layers. In fact, convolutional layers are fully connected layers, in which some of the weights are set to zero and some weights are shared between neurons.