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.