Generative Adversarial Network

Generative Adversarial Networks (GANs) consist of two neural networks: a generator that creates data and a discriminator that evaluates the authenticity of the generated data. The generator aims to produce data that is indistinguishable from real data, while the discriminator strives to accurately identify real versus generated samples. This adversarial process leads to the creation of high-quality synthetic data.