Convolution layer (CONV) The convolution layer (CONV) uses filters that perform convolution functions as it is scanning the enter $I$ with respect to its dimensions. Its hyperparameters include things like the filter size $F$ and stride $S$. The ensuing output $O$ is called aspect map or activation map. > https://financefeeds.com/carv-announces-the-launch-of-carv-svm-chain-testnet-empowering-ai-agents-redefining-data-sovereignty/