Convolution Layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution operations as it truly is scanning the enter $I$ with respect to its dimensions. Its hyperparameters incorporate the filter size $File$ and stride $S$. The ensuing output $O$ is called characteristic map or activation map. https://financefeeds.com/dreamcars-makes-fractional-ownership-of-luxury-cars-a-reality-users-to-earn-monthly-passive-income/