Convolution layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution operations as it really is scanning the input $I$ with respect to its dimensions. Its hyperparameters consist of the filter size $File$ and stride $S$. The resulting output $O$ is called feature map or activation https://financefeeds.com/top-7-meme-coins-to-invest-in-now-explosive-copyright-picks-of-2025/