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.
Previously at
Darko Simic
Fullstack Developer
Previously at
Lana Ilic
Fullstack Developer
Previously at
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