Convolution layer (CONV) The convolution layer (CONV) makes use of filters that perform convolution functions as it is scanning the input $I$ with respect to its Proportions. Its hyperparameters contain the filter size $F$ and stride $S$. The ensuing output $O$ is called feature map or activation map. A https://financefeeds.com/bitcoin-records-new-all-time-high-of-106000-best-cryptos-to-buy-now/