Overview of Generative Adversarial Network in Noise Removal

Abstract

A generative model such as Generative Adversarial Network (GAN) has achieved awesome success in the region of image classification, signal processing, etc. GANs models are used to provide the new samples which have same data representation for the training dataset. The process of GAN will be introduced in this article, followed by the various types of GANs will be explained and also its comparative details will be represented. After that, the applications of GANs will be discussed in this article.