Convolution layer (CONV) The convolution layer (CONV) makes use of filters that perform convolution functions as it truly is scanning the enter $I$ with regard to its dimensions. Its hyperparameters consist of the filter size $F$ and stride $S$. The ensuing output $O$ is called attribute map or activation https://financefeeds.com/because-they-asked-plus-wallet-users-can-now-trade-trump-as-phantom-wallet-raises-150m-bitget-event-hosts-token-sale/