Fake Image Generation Using Deep Convolutional Generative Adversarial Networks (DCGANs)

Fake Image Generation Using Deep Convolutional Generative Adversarial Networks (DCGANs)

Mohit Joshi*
* Department of School of Computing, Graphic Era Hill University

Abstract- As computing power has developed over the years, various generative models have also been created in the machine learning field. One particularly well-liked generative model, known as Generative Adversarial Networks, has only recently been introduced and studied among all these generative models. It is predicated on the idea of two competitors who are always attempting to exceed one another. The goal of this review is to thoroughly analyse the GAN-related literature and present a concise version of the literature that has been studied on GAN, including the idea behind it, its primary function, proposed base model modifications, and current trends in this field of study. This paper is intended to help in providing a comprehensive understanding of GAN