Convolution layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution functions as it can be scanning the input $I$ with respect to its dimensions. Its hyperparameters include the filter size $F$ and stride $S$. The ensuing output $O$ is called characteristic map or activation map.Every layer while in the neural