Convolution layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution functions as it is actually scanning the enter $I$ 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/arbitrum-60-downs-looks-like-failing-tech-is-about-to-be-over-shadowed-by-1fuel-exchange-2/