DCGAN: Deep Convolutional Generative Adversarial Network
Want to know what is DCGAN, the difference between GAN and DCGAN, GAN applications, and implementation of DCGAN on Fashion MNIST then read on…
Prerequisites:
A basic understanding of CNN and a sample implementation using CNN
What is GAN?
GAN is Generative Adversarial Network having two neural networks: Generator and Discriminator that are pitted against each other and are simultaneously trained by an adversarial process.
GAN has two key networks
Generator: learns to generate plausible data that is very similar to the training data. Data generated from the Generator should be indistinguishable from the real data.
Discriminator: the key objective is to distinguish between the generator’s fake data from the real data and is a simple classification network.
The Generator acts like a forger trying to trick the Discriminator by generating fake data. The Discriminator acts like a cop trying to differentiate. Between fake data and real data and in…
