Discriminator
A Discriminator is a neural network component within a Generative Adversarial Network (GAN) architecture. Its role is to evaluate inputs and classify them as either "real" (originating from the true training dataset) or "fake" (produced by the generator network).
Frequently Asked Questions
How does the discriminator improve the generator?▼
By acting as an adversary. As the discriminator gets better at spotting fakes, the generator is forced to produce more realistic images to fool it.
What is the output of a discriminator network?▼
A single probability score between 0 and 1, representing the model's confidence that the input is a genuine real-world sample.
Quick Facts
- CategoryGenerative AI
- Key ApplicationGAN model training, classification auditing, and authentic data verification.
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