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other than convolutional layers confidence often also use pooling layers to reduce the size of the representation to speed the computation as well as make some of the features it detects a bit more robust lets take a look lets go through an example of pooling and then well talk about why you might want to do this suppose you have a four by four input and you want to apply a type of pooling called max pooling and the output of this particular implementation of max pooling will be a two by two output and the way you do that is quite simple take your four by four input and break it into different regions and Im going to cover the four regions as follows and then in the output which is two by two each of the outputs will just be the mask from the correspondingly shaded region so in the upper left I guess the max of these four numbers is nine upper right the max of the blue numbers is 2 lower left the biggest number is six and lower right to the biggest number is three so to compute ea