Convolution layer (CONV) The convolution layer (CONV) makes use of filters that perform convolution operations as it is actually scanning the enter $I$ with regard to its Proportions. Its hyperparameters include the filter size $F$ and stride $S$. The resulting output $O$ is called attribute map or activation map. https://financefeeds.com/are-ai-tokens-rising-in-popularity-which-altcoin-would-like-buying-sol-at-10/