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Smart Attendance and Progress Management System

机译:智能出勤和进度管理系统

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摘要

Management of attendance may be a great burden on lecturers if done manually. This study focuses on finding an automated solution for taking attendance and keeping track of progress of a student in a smart way. The smart attendance system is generally using biometrics for identifying individuals. In this study, face recognition was considered for identification. The student's face is recognized and attendance is taken using face biometrics based on high-definition monitor camera. The images of the student are given as an input and image classification was done using CNN algorithm preventing duplicate entries for attendance. For tracking the progress of the student, the factors affecting the GPA are trained using Machine Learning algorithms. This research also aims to examine the effective progress of undergraduate students by taking past year records and find out the factors for their high and low output which will be helpful to improve their performance.
机译:如果手动完成,出勤管理可能是讲师的巨大负担。 本研究侧重于寻找以智能方式考虑和跟踪学生进度的自动化解决方案。 智能考勤系统通常使用生物识别来识别个人。 在这项研究中,考虑了面部识别进行鉴定。 学生的脸被认可,并使用基于高清监视器相机的面部生物识别来进行出勤。 将学生的图像作为输入和图像分类给出,使用CNN算法来防止重复的出勤条目。 为了跟踪学生的进度,使用机器学习算法训练影响GPA的因素。 本研究还旨在通过过去的一年记录来研究本科生的有效进展,并找出他们的高度和低产量的因素,这将有助于提高其性能。

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