Question: How do Generative Adversarial Networks ( GANs ) differ from other neural networks in their architecture and applications? GANs use single networks for pattern matching

How do Generative Adversarial Networks (GANs) differ from other neural networks in their architecture and applications?
GANs use single networks for pattern matching
GANs require less training data than other networks
GANs compete to improve accuracy through opposition
GANs focus only on classification tasks
How do Generative Adversarial Networks ( GANs )

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