Convolution layer (CONV) The convolution layer (CONV) works by using filters that perform convolution operations as it is scanning the enter $I$ with respect to its dimensions. Its hyperparameters include things like the filter size $F$ and stride $S$. The ensuing output $O$ is called attribute map or activation https://financefeeds.com/tmx-group-launches-alphax-us-its-first-us-equity-alternative-trading-system/