Enhancing Attendance Management: A Novel Approach Using Advanced Face Recognition Technology
Authors: Dr. Ayesha Heena & Mohsina Banu
This research presents an automated Face Recognition Attendance System (FRAS) engineered to improve recognition accuracy, operational throughput, and real-time biometric management using deep Convolutional Neural Networks (CNNs).
The paper explores image preprocessing, multi-angle feature embedding, and verification across diverse ambient lighting conditions. The proposed system achieved an overall recognition accuracy of 98.5% with an average recognition latency of 0.5 seconds.