Deep Learning-Based Automatic Student Authentication

Abstract

Classroom management relies heavily on the ability to keep track of student attendance. Attendance checks by calling names or handing out a sign-in sheet are time-consuming and vulnerable to fraud, especially the latter. Data science and image processing are the focus of this regarding counting the number of people present at a gathering for various objectives, such as determining a person's duty status, determining a person's physical presence in a classroom, determining a person's security clearance to enter a meeting hall, etc. It takes a lot of time and effort to maintain a database for future use when generating attendance records using the standard technique. With the help of the latest technology, attendance can be entered automatically. It is a frequently used face recognition technique that generates a binary code for each cell and compares it to the reference image. With the use of deep learning, this LBP method has been reworked in order to automate attendance generation.