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Comparative Study on Generative Adversarial Networks - 2018

Comparative Study On Generative Adversarial Networks

Survey Paper on Generative Adversarial Networks

Research Area:  Machine Learning

Abstract:

In recent years, there have been tremendous advancements in the field of machine learning. These advancements have been made through both academic as well as industrial research. Lately, a fair amount of research has been dedicated to the usage of generative models in the field of computer vision and image classification. These generative models have been popularized through a new framework called Generative Adversarial Networks. Moreover, many modified versions of this framework have been proposed in the last two years. We study the original model proposed by Goodfellow et al. as well as modifications over the original model and provide a comparative analysis of these models.

Keywords:  
Generative Adversarial Networks
Machine Learning
Deep Learning

Author(s) Name:  Saifuddin Hitawala

Journal name:  Computer Science

Conferrence name:  

Publisher name:  arXiv:1801.04271

DOI:  10.48550/arXiv.1801.04271

Volume Information: