HFDCM: A low-cost machine learning based class attendance monitoring system

In this paper, a unique camera model was proposed to evaluate class attendance more efficiently. For making the system more robust and reliable, attendance was taken after 15 minutes of class starts and before 15 minutes of class ending. A unique algorithm was also proposed to operate the system properly. This system uses a state-of-the-art methodology to evaluate students attendance. Which is actually based on face detection and face recognition. Accuracy in percentage was the primary concern for choosing the more accurate methodology.