Dynamic attendance system using face recognition via machine learning models - Upadhyay, Nishant; Bansal, Nidhi; Velinov, Emil; Harshit, Harshit; Sharma, Abhay; Kumar, Sanjeev (Institute of Advanced Engineering and Science, 2025)
Traditional methods to handle attendance have been implemented in the schools in the past and most of them are discouraging as they require that the institutions implement the use of paper and pen to get the results. To enhancing effectiveness and safeguarding, this paper presents a face recognition attendance system that mechanizes the usual attendance taking process. Using best practices in facial recognition, the system captures images of students’ faces, stores them, feeds them into a recognition model, and uses real-time facial recognition to mark attendance. This means that the system enjoys data encryption and password protected access that ensures data is safe. In the proposed system, the OpenCV face recognition libraries combined with machine learning algorithms for better face recognition ability with better efficiency. The results confirm that the system provides a reliable approach to handling attendance and it may debut in various contexts.