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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM53416

Face Based Student Attendance System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM53416

Volume:

9 |

11 |

Nov 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM53416

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

LK

Lakshmanan K1

DG

Deebanchakkarawarthi G2

SS

Sathya S3

PG

Priyadarshini G4

MIM

Mohamed Ifran M5

MM

Muvitha M6

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Abstract

The Face-Based Student Attendance System is an innovative application of artificial intelligence and computer vision designed to automate the traditional attendance process in educational institutions. Instead of manual roll calls or biometric devices, the system uses facial recognition technology to identify and record student attendance accurately. By capturing facial features through a camera and comparing them with stored data, the system ensures high accuracy and eliminates the chances of proxy or fake attendance. It also saves time, reduces human effort, and provides a contactless and hygienic method of attendance tracking. This system helps teachers and administrators manage attendance records efficiently while promoting the use of modern technology in academic management.

KEYWORDS

Face Recognition Attendance System Artificial Intelligence (AI) Machine Learning (ML) Deep Learning Image Processing Computer Vision OpenCV Automation Convolutional Neural Network (CNN) Real-Time Detection Biometric Authentication Student Management System.

Cite This Article

Lakshmanan K1, Deebanchakkarawarthi G2, Sathya S3, Priyadarshini G4, Mohamed Ifran M5, Muvitha M6, "Face Based Student Attendance System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 11, Nov 2025. https://doi.org/10.55041/IJSREM53416

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Publication Date

4/10/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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3

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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