Publication

Abstract : The conventional methods of attendance management that involve manual processes, are prone to errors and time-consuming. In the rapidly evolving landscape of technology, integration of artificial intelligence and computer vision has led to groundbreaking advancements in various domains. One such application that holds significant promise is the development of facial recognition-based attendance system. This paper focuses on the development of artificial intelligence-based attendance logging and tracking system. The proposed system includes capture, face identification, face extraction, comparison, and classification units. The system employs Haar Cascade classifiers, a robust object detection technique, to identify and extract faces. The webpage provides a user-friendly platform for the students to check the attendance details by providing the login credentials. The proposed attendance logging system is tested for its effective performance by providing different student images.