Tag: GANs

Deep Learning – Introduction to Generative Adversarial Neural Networks (GANs)

GANs consist of two neural networks i.e. Generator that generates a fake image of our currency note example and a disa criminator that classifies it into real or fake. The generator’s role is to map the input to the desired data space (image as in the example above). On the other hand second neural network models i.e. the discriminator classify the output with probability as real or fake compared with real datasets.