generative-adversarial-networks

Generative Adversarial Networks (GANs) consist of two neural networks, a generator and a discriminator, that compete against each other in a game-theoretic framework. The generator creates new data samples, while the discriminator evaluates their authenticity. This framework excels in generating realistic images, text, and audio. A misconception is that GANs can only generate realistic images; they can also be used for diverse applications including video generation and data augmentation.