Convolution layer (CONV) The convolution layer (CONV) uses filters that perform convolution functions as it can be scanning the input $I$ with respect to its Proportions. Its hyperparameters contain the filter size $F$ and stride $S$. The resulting output $O$ is called aspect map or activation map. Computer Vision: https://financefeeds.com/navigating-the-secs-rule-changes-to-treasury-clearing/