Convolution layer (CONV) The convolution layer (CONV) works by using filters that perform convolution functions as it is scanning the enter $I$ with respect to its dimensions. Its hyperparameters contain the filter size $F$ and stride $S$. The resulting output $O$ is called attribute map or activation map. Bogle’s https://financefeeds.com/tradu-launches-spread-betting-in-the-united-kingdom/