Authors :
Amith D V; Chandana V; Krupesha D; Keshava B; Abhishek Gowda S
Volume/Issue :
Volume 8 - 2023, Issue 5 - May
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://t.ly/AggO8
DOI :
https://doi.org/10.5281/zenodo.7968809
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.
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.
