GANs make use of two networks:
- Generator network
- Discriminator network
For the generator network, noisy data, which is usually random numbers that have been generated from a standard normal distribution are provided as input. A flow chart showing an overview of a generative adversarial network is as follows:
As indicated in the preceding flowchart, the generator network uses noisy data as input and tries to create an image that we can label as fake. These fake images, along with the labels representing them as fake, are provided as input to the discriminator network. Along with the labeled fake images, we can also provide real images with labels as input to the discriminator network.
During the training process, the discriminator network tries to differentiate between a fake image created by the generator network and a real image. While...
