Affiliation:
1. Sandip University, Nashik, India
2. Vishwakarma Institute of Information Technology, Pune, India
3. Vishwakarma Institute of Technology, Pune, India
Abstract
Facial recognition technology has emerged as a critical tool in public safety, aiding surveillance, law enforcement agencies, identity verification, and even social media platforms. However, traditional facial recognition systems often face challenges related to accuracy and privacy. This chapter explores how Generative Adversarial Networks (GANs) have revolutionized facial recognition, offering solutions to improve accuracy while addressing privacy concerns. By augmenting datasets, enhancing features, and preserving privacy, GANs represent a significant advancement in public safety applications.
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