Before moving forward, let's have a look at the architecture of the discriminator network:
The preceding diagram gives a top-level overview of the architecture of the generator network.
As mentioned, the discriminator network is a CNN that contains 10 layers (you can add more layers to the network according to your requirements). Basically, it takes an image of dimensions of 64 x 64 x 3, downsamples it using 2D convolutional layers, and passes it to the fully connected layers for classification. Its output is a prediction as to whether the given image is a fake image or a real image. This can be either ...
