Explain the Max Pool Layer

Data Science, AI and ML
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#1

Max Pool Layer

#2

Maximum pooling, or max pooling, is a pooling operation that calculates the maximum, or largest, value in each patch of each feature map.

The results are down sampled or pooled feature maps that highlight the most present feature in the patch, not the average presence of the feature in the case of average pooling. This has been found to work better in practice than average pooling for computer vision tasks like image classification.
ref:https://www.quora.com/What-is-max-pooling-in-convolutional-neural-networks