Convolution layer (CONV) The convolution layer (CONV) uses filters that perform convolution operations as it truly is scanning the enter $I$ with regard to its dimensions. Its hyperparameters include things like the filter size $F$ and stride $S$. The ensuing output $O$ is called attribute map or activation map. https://financefeeds.com/altcoins-will-reign-supreme-this-year-here-are-the-5-top-cryptos-to-buy-in-2025-blockdag-toncoin-solana-more/