Pooling layer

Accepts as input:

Outputs another feature vector of size $W_2&space;\times&space;H_2&space;\times&space;D_1$ , where Accepts as input: The pooling resizes independently every channel of the input feature vector by applying a certain function on neighbourhoods of size $F&space;\times&space;F$ , with a stride $S$ .
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Max pooling

Picks the maximal value from every neighbourhood.

Average pooling

Computes the average of every neighbourhood.

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