Convolution Layer (CONV) The convolution layer (CONV) uses filters that perform convolution functions as it can be scanning the input $I$ with regard to its dimensions. Its hyperparameters include things like the filter size $F$ and stride $S$. The ensuing output $O$ is called feature map or activation map. https://financefeeds.com/binances-2024-year-in-review-driving-innovation-and-expanding-access-in-the-blockchain-industry/