What is the pooling operation on CNN?

Pooling Layer:

• It is commonly used to periodically insert a Pooling layer in-between successive Conv layers in a ConvNet architecture.

• Its function is to progressively reduce the spatial size of the representation to reduce the number of parameters and computations in the network and hence also control overfitting.

• The Pooling Layer operates independently on every depth slice of the input and resizes it spatially, using the MAX operation.

• The most common form is a pooling layer with filters of size 2x2 applied with a stride of 2 downsamples of every depth slice in the input by two along both width and height, discarding 75% of the activations.

• Every MAX the operation would, in this case, be taking a max over four numbers (little 2x2 region in some depth slice). The depth dimension remains unchanged.