Convolution layer (CONV) The convolution layer (CONV) makes use of filters that perform convolution functions as it's scanning the input $I$ with respect to its dimensions. Its hyperparameters include things like the filter size $F$ and stride $S$. The resulting output $O$ is called attribute map or activation map. https://financefeeds.com/copyright-gems-must-watch-copyright-assets-for-january-2025-monsta-mash-mash-myria-myria-celo-celo/