Average pooling

Average pooling is a technique used in deep learning, particularly in convolutional neural networks, to reduce the spatial dimensions of an input feature map. It works by taking the average of elements within a specified window (or kernel) and then sliding this window across the entire feature map to create a new, reduced feature map.