Face Recognition for Attendance System in Online Classes

Attendance management is an important task in educational institutes as it reflects in the academic performance of a student. Upon observation, it was found that a considerable amount of time is being spent in this process (which has a repetitive nature) and a need of automating this process is realized. The main idea discussed in this paper is to use deep learning techniques to automatically identify the students present in a class and mark their attendance. Convolutional neural network (CNN) was being applied to detect the faces visible in the frame which was then used to recognize students present and mark their attendance. The proposed architecture was applied in the online mode of teaching, and the best accuracy of 76% was being recorded using the FaceNet model, while the best precision of 88% was being recorded using the VGG-Face model. These best-performing CNN models can be considered as an effective tool for face recognition to enhance the current attendance recording system.