Abstract

Facial recognition technology has witnessed significant progress in recent years, with a particular emphasis on improving accuracy, privacy, and efficiency. This research paper delves into the development of a facial recognition system that not only excels in recognizing faces in real-life scenarios but also prioritizes privacy concerns by differentiating between real faces and images. The system is designed to operate swiftly in various settings, including live videos and security cameras, catering to both large-scale and resource- constrained environments. By incorporating machine learning techniques, the system continuously evolves to handle new challenges effectively, making it a valuable tool for applications such as attendance tracking in educational institutions