Convolution layer (CONV) The convolution layer (CONV) works by using filters that perform convolution functions as it is scanning the enter $I$ with regard to its Proportions. Its hyperparameters include the filter size $File$ and stride $S$. The resulting output $O$ is called feature map or activation map. > https://financefeeds.com/global-fx-market-summary-eurozone-economic-data-trumps-tariff-speculations-political-and-market-dynamics-6-january-2025/