Convolution layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution operations as it truly is scanning the input $I$ with regard to its dimensions. Its hyperparameters involve the filter size $File$ and stride $S$. The resulting output $O$ is called attribute map or activation map. https://financefeeds.com/floki-scores-pitchside-ad-campaign-in-rugby-super-league/