The Role of Generative Adversarial Networks in Transforming Creative Industries: Innovations and Implications

Authors

  • Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, Uday Krishna Padyana, Hitesh Premshankar Rai, Pavan Ogeti

Keywords:

Generative Adversarial Networks (GANs), deep learning, human creativity, economic implications, social implications, model training methods, copyright, authorship, GAN architecture, ethical frameworks, AI integration

Abstract

This research report mainly emphasizes the transformational impacts of the Generative Adversarial Networks (GANs) technology that are related to the creative industries, including the music, art, fashion, and other filmmaking industries. It mainly leverages deep learning technology and mimics human creativity pushing the boundary of the creativity fields. It contains different highlights that enhance the social and economic implications through model training methods that address the authorship, and copyright and also preserve traditional human creativity. Thus it concludes the enhancement of the GAN architecture and includes the development of the ethical frameworks that foster interdisciplinary collaboration through AI integration.

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Published

17.05.2023

How to Cite

Narendra Sharad Fadnavis. (2023). The Role of Generative Adversarial Networks in Transforming Creative Industries: Innovations and Implications. International Journal of Intelligent Systems and Applications in Engineering, 11(6s), 849–855. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6727

Issue

Vol. 11 No. 6s (2023)

Section

Research Article

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