Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{157054,
        author = {Vinil Gupta and Devesh C Singhal and Aby Anthony and Aishwarya Funaguskar and Rishav Tiwari and Sparsh Gaba and Patel Abdullah Zuber},
        title = {Mythological Figures Face Prediction Using Generative Adversarial Networks },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {5},
        pages = {823-827},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=157054},
        abstract = {A potent style of neural network called generative adversarial networks is used to generate new data from a collection of training data that maintains the same characteristics as the training data. It has a wide variety of applications, (with some of them not being as noble as others) for animation ranging from animation model generation to deepfake generation. In this paper, we propose the application of GANs to generate realistic images of a mythological being depending on the existing depictions from various artists in the same period. },
        keywords = {Generative Adversarial Networks, Unsupervised Machine Learning, Neural Networks, Deep Learning},
        month = {},
        }