Meaning of Generative Adversarial Networks (GANs)

Simple definition

Generative Adversarial Networks (GANs) are a type of neural network architecture that consists of two models – a generator and a discriminator – which work against each other to create realistic data, such as images or videos.

How to use Generative Adversarial Networks (GANs) in a professional context

GANs are used in image and video generation, art creation, and deepfake technology.

Concrete example of Generative Adversarial Networks (GANs)

GANs can generate realistic images of people who don’t exist by training on a dataset of real human images.