Pooling Layer

Pooling layers reduce the spatial resolution of feature maps, lowering both computational cost and sensitivity to small positional changes. Max pooling and average pooling are the most well-known examples. These layers were used extensively in early CNN architectures. Although some modern designs replace them with strided convolutions in certain tasks, they remain conceptually important.