Convolution Layer (CONV) The convolution layer (CONV) uses filters that perform convolution operations as it can be scanning the input $I$ with regard to its dimensions. Its hyperparameters involve the filter size $F$ and stride $S$. The ensuing output $O$ is called attribute map or activation map. > Risks: https://financefeeds.com/bitnomial-launches-digital-asset-clearinghouse-bnch/