AUTOMATIC STUDENT ATTENDANCE APPLICATIONS USING FACIAL RECOGNITION TECHNIQUES

Abstract

Image recognition is one of the major and classic problems in the field of computer vision and image processing. The purpose of image recognition is to determine whether or not special objects exist in the image. In this thesis, we focus on human facial recognition techniques and build an automated student attendance application using facial recognition. The topic "Automatic student attendance applications using facial recognition techniques" allows managing part class schedules and automatically taking attendance while the lecture is in class. The application allows students to be enrolled using facial recognition technology through class photos at the desired time of the teacher. We study the method of image classification and recognition based on the Yolov3 model. The topic allows recognition of faces through group photos of students in the classroom and return results to serve the attendance of the classes.