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 dimensions. Its hyperparameters include things like the filter size $File$ and stride $S$. The ensuing output $O$ is called aspect map or activation map. https://financefeeds.com/best-copyright-to-buy-solaxy-raises-14-5m-for-first-solana-layer-2-chain/