Publication Date: 2023/05/25
Abstract: A project employing machine learning to track student attendance in schools is the attendance management and student tracking system using facial recognition. Each student's face is captured by a camera as they enter the classroom, and the system compares that image to the student's previously saved information to record their attendance. To develop a distinctive template for each student that is utilised for recognition, the system uses deep learning algorithms to extract information from the faces. Additionally, the system has the ability to recognise many faces at once and may record multiple pupils' attendance in a single frame. The technology tracks student movement throughout the classroom and gives the teacher with real-time data about student behaviour and activities in addition to managing attendance. The system makes use of this information to produce reports and analytics that administrators and teachers may use to assess student performance and make informed decisions. Overall, the facial recognition-based attendance and student tracking system offers a creative approach to streamlining classroom management and raising student achievement.
Keywords: Machine Learning, Facial Recognition, Support Vector Machine, Haar Cascade.
DOI: https://doi.org/10.5281/zenodo.7968809
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23MAY1464.pdf
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