Convolution layer (CONV) The convolution layer (CONV) makes use of filters that perform convolution functions as it can be scanning the enter $I$ with respect to its Proportions. Its hyperparameters involve the filter size $File$ and stride $S$. The ensuing output $O$ is called function map or activation map. https://financefeeds.com/3-cryptos-positioned-for-18x-gains-in-2025-and-none-are-bitcoin-btc-or-dogecoin-doge/