Convolution layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution operations as it is scanning the input $I$ with regard to its dimensions. Its hyperparameters incorporate the filter size $F$ and stride $S$. The resulting output $O$ is called element map or activation map.The LeNet architecture is simple and