Convolution Layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution operations as it can be scanning the enter $I$ with respect to its dimensions. Its hyperparameters involve the filter size $File$ and stride $S$. The ensuing output $O$ is called attribute map or activation map. https://financefeeds.com/decembers-top-copyright-picks-to-kickstart-2025/