What does the discriminator do in a GAN?Creates imagesEnhances image resolutionEvaluates if an image is real or fakeCombines imagesBoth create and evaluate images

In Conditional GANs (cGANs), what additional information is provided to both the generator and discriminator during training?Question 20Answera. Image gradientsb.Noise vectorc.Latent space vectorsd.Class labels

In a GAN (Generative Adversarial Network), the network is responsible for generating new data, while the network tries to distinguish between real and generated data.

Which of the following best describes the role of the generator in a GAN?To critique imagesTo produce imagesNone of the given optionsTo combine imagesTo evaluate the loss

In a Generative Adversarial Network (GAN) training session, the discriminator evaluates 800 samples. Out of these, it correctly identifies 680 samples as real and 100 samples as fake. What is the discriminator’s accuracy in percentage?

Why might someone want to use GANs on the CIFAR-10 dataset?To delete images from the datasetTo classify the images in the datasetTo critique the images in the datasetTo reduce the size of the datasetTo generate novel and relevant images to augment dataset