Convolution layer (CONV) The convolution layer (CONV) works by using filters that perform convolution functions as it really is scanning the input $I$ with respect to its Proportions. Its hyperparameters contain the filter size $File$ and stride $S$. The ensuing output $O$ is called attribute map or activation map. https://financefeeds.com/pick-the-right-coin-for-your-portfolio-here-are-the-top-5-cryptos-to-buy-right-now-bdag-xrp-doge-bnb-link/