Convolution layer (CONV) The convolution layer (CONV) utilizes filters that perform convolution functions as it is scanning the enter $I$ with respect to its dimensions. Its hyperparameters include the filter size $File$ and stride $S$. The resulting output $O$ is called feature map or activation map. According to research https://financefeeds.com/uk-and-ny-financial-authorities-partner-to-share-know-how-on-copyright/