Convolution layer (CONV) The convolution layer (CONV) takes advantage of filters that perform convolution functions as it is scanning the enter $I$ with respect to its Proportions. Its hyperparameters involve the filter size $File$ and stride $S$. The ensuing output $O$ is called feature map or activation map. Personal https://financefeeds.com/33-copyright-etfs-filed-as-gary-gensler-resigns-from-sec-time-to-buy-xrp-sol-meme-coins/