Convolution layer (CONV) The convolution layer (CONV) uses filters that perform convolution operations as it is actually scanning the input $I$ with regard to its Proportions. Its hyperparameters consist of the filter size $F$ and stride $S$. The resulting output $O$ is called attribute map or activation map. Variational https://financefeeds.com/bitcoin-price-prediction-leak-reveals-imminent-trump-game-changer-to-200000/