Convolution layer (CONV) The convolution layer (CONV) uses filters that perform convolution functions as it's scanning the input $I$ with respect to its Proportions. Its hyperparameters contain the filter size $File$ and stride $S$. The resulting output $O$ is called characteristic map or activation map. A convolutional neural network, https://financefeeds.com/2025-is-looking-bullish-for-altcoins-here-are-the-5-top-cryptos-to-buy-now-blockdag-polkadot-near-protocol-tron-toncoin/