Attendance Monitoring System Using Face Recognition
H K Shashikala, Abhinav Singh Upreti, Shreya Nupur Shakya, Shaik Dadapeer, Pooja Panjiyar · Zenodo (CERN European Organization for Nuclear Research) · 2022
In today’s tech-savvy academic establishments, attending is taken into account as a crucial issue for each student and institutional authorities. However, professors are still compelled to bear manual procedures to record attendance data, which is very slow and inefficient. Among all biometric ways, the machine-driven personality authentication systems supported face recognition is understood to be the foremost reliable one. With the rise within the development of face recognition systems, there are many proposals for varied applications, together with the attending management system. In addition, problems concerning proxy attending, inaccuracy, and students’ unconsciousness of their attending standing arise undeniably. The projected project aims at developing a system that may facilitate professors' present watching of a classroom. This project additionally aspires to create flexibility for college kids to look at their data, attending standing, college data, and timetable. Once totally enforced, we tend to believe the system can assist in dynamic the standard attending management system into associate degree correct and economical system. Moreover, the system can utilize and implement ideas of deep learning to create a much better system compared to the present ones.