Enhancing generative adversarial network

Rajbeer Kaur; Amanpreet Kaur; Kirandeep Kaur

doi:10.30574/gjeta.2024.19.1.0057

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Enhancing generative adversarial network

Rajbeer Kaur ^*, Amanpreet Kaur and Kirandeep Kaur

Department of Computer Application, Global Group of Institutes, Amritsar, India.

Research Article

Global Journal of Engineering and Technology Advances, 2024, 19(01), 068–073.

Article DOI: 10.30574/gjeta.2024.19.1.0057

DOI url: https://doi.org/10.30574/gjeta.2024.19.1.0057

Publication history

Received on 24 February 2024; revised on 01 April 2024; accepted on 04 April 2024

Abstract

The paper provides a comprehensive review of various GAN methods from the perspectives of theory, and applications. GAN algorithms' mathematical representations, and structures are detailed. The commonalities and differences among these GANs methods are compared. Theoretical issues related to GANs are explored, and typical applications in various fields are showcased. Future scope of research problems for GANs are also discussed in the paper.

Keywords

introduction of Generative adversarial network; Working of GAN; Structure of Generative adversarial network; Steps to improve generative adversarial network

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How to cite this article

Rajbeer Kaur, Amanpreet Kaur and Kirandeep Kaur. Enhancing generative adversarial network. Global Journal of Engineering and Technology Advances, 2024, 19(1), 068-073. Article DOI: https://doi.org/10.30574/gjeta.2024.19.1.0057

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