Convolution layer (CONV) The convolution layer (CONV) works by using filters that perform convolution functions as it can be scanning the input $I$ with respect to its dimensions. Its hyperparameters contain the filter size $F$ and stride $S$. The resulting output $O$ is called element map or activation map. https://financefeeds.com/bitpanda-secures-micar-license-from-german-regulator-bafin/