Convolution layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution operations as it can be scanning the enter $I$ with respect to its dimensions. Its hyperparameters involve the filter size $F$ and stride $S$. The resulting output $O$ is called element map or activation map. https://financefeeds.com/koni-stack-launches-football-rivals-on-telegram-onboarding-millions-of-users-to-mythos-polkadot/