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

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-5948-55	editor@ijfmr.com

International Journal For Multidisciplinary Research