Average pooling is a downsampling technique used in Convolutional Neural Networks (CNNs) to reduce the spatial dimensions of feature maps while retaining important information. By calculating the average of a defined region in the input feature map, this method helps to decrease the amount of data and computation in the network, which can improve performance and reduce overfitting.
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