GANs consist of two neural networks, a generator, and a discriminator, that are trained simultaneously. The generator aims to create data that is similar to a given dataset, while the discriminator’s role is to distinguish between real and generated data. This adversarial training process results in the generator improving its ability to produce realistic content.
- Badges
- Science topic
More Anis Hamza's questions See All
Similar questions and discussions