Convolution layer (CONV) The convolution layer (CONV) works by using filters that perform convolution functions as it's scanning the input $I$ with respect to its Proportions. Its hyperparameters consist of the filter size $File$ and stride $S$. The resulting output $O$ is called attribute map or activation map. * https://financefeeds.com/re-modelled-wallet-exchange-1fuel-rivals-solana-xrp-in-100x-bull-run/