Deep Learning By Example

The pooling step

One of the important steps for our learning process is the pooling step, which is sometimes called the subsampling or downsampling step. This step is mainly for reducing the dimensionality of the output of the convolution step (feature map). The advantage of this pooling step is reducing the size of the feature map while keeping the important information in the newly reduced version.

The following figure shows this step by scanning the image with a 2 by 2 filter and stride 2 while applying the max operation. This kind of pooling operation is called max pool:

Figure 9.8: An example of a max pooling operation on a rectified ...