International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 3 May-June 2024 Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

Exploring Generative Adversarial Networks for Face Generation

Author(s) Deepanshu Koli, Anmol Singal, Dr. Amita Goel, Dr. Vasudha Bahl, Ms. Nidhi Sengar
Country India
Abstract This research has used Generative Adversarial Networks (GANs) for face generation in the area of the research [1]. GANs have demonstrated a high effectiveness in imitation of natural images not only, but also in specific applications [2]. For the succeeding paper, their potential especially on creating human faces are being looked into. The primary goal is to develop a new design and practical training strategy to efficiently produce high-quality facial images [3]. Experimental results confirm the ability of the proposed method to generate artificially intelligent faces and its role in improving the quality of the images.
Keywords Generative Adversarial Networks, Face Generation, Text-to-Image Synthesis, Deep Learning, Neural Networks, Evaluation Metrics, Data Augmentation, Face Recognition, Natural Language Processing
Field Engineering
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-05-11
Cite This Exploring Generative Adversarial Networks for Face Generation - Deepanshu Koli, Anmol Singal, Dr. Amita Goel, Dr. Vasudha Bahl, Ms. Nidhi Sengar - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.20002
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.20002
Short DOI https://doi.org/gttvdb

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