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 involve the filter size $F$ and stride $S$. The ensuing output $O$ is called attribute map or activation map. Knowledge https://financefeeds.com/5-best-new-meme-coin-presales-to-invest-in-for-long-term-the-presale-opportunity-you-cant-afford-to-miss/