The following screenshot shows the architecture of a popular CNN called VGG-16/19. The remarkable thing about the VGG-16 net is that, instead of having so many hyper-parameters, it lets you use a much simpler network where you focus on just having convolutional layers that are just 3 x 3 filters with a stride of 1 and that always use the same padding and make all the max pooling layers 2 x 2 with a stride of 2. It is a really deep network.
This network has a total of about 138 million parameters, as seen in the following diagram:
