GAN (Generative Adversarial Network)

Generative Adversarial Networks (GANs) are AI models consisting of two neural networks—a generator and a discriminator—that compete against each other to create highly realistic synthetic data. GANs are widely used in image generation, deepfake creation, and AI-based art.

Key Features:

  • Dual-network system – A generator creates images, while a discriminator evaluates them.

  • Self-improving – Models refine outputs over time.

  • High realism – Generates lifelike images and videos.

  • Broad applications – Used in entertainment, security, and data augmentation.

Best Use Cases:

  • Deepfake technology.

  • AI-generated art and media.

  • Augmenting datasets for AI training.

  • Medical imaging enhancements.

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