Generative Adversarial Networks (GANs) consist of two main components: a generator network and a discriminator network. The generator network generates synthetic data samples, while the discriminator network aims to distinguish between real and fake data. The two networks are trained simultaneously in an adversarial process, pushing each other to improve their performance. Here is a detailed explanation of the architecture and components of GANs.
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