Generative Adversarial, Deep Learning, Artificial Intelligence, Naturallanguageprocessing.
combinations. This is done by considering any generated image that is not consistent with the sample data as an adversarial example (thus the name of the network). Below is the high-level schematic of what a GAN looks like: Random data is generated, and passed to the Discriminator network that is