Attendance Management System Using Facial Recognition

Krishnan, Padmaveni; Manikuttan, Athira

doi:10.1109/ic3sis54991.2022.9885693

Cited by 6 publications

(3 citation statements)

References 10 publications

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“…[5] Mansi Singhal and Gufran Ahmad (2023) likely delve into deep learning-based real-time face recognition for university attendance systems, exploring practical applications of advanced technologies in educational settings. [6] P Sarath Krishnan and Athira Manikuttan (2022) offer insights into attendance management systems using facial recognition technology, discussing the state of the art in 2022 and technical aspects of system implementation. [7] Isha Rajput et al ( 2022) likely discuss an attendance management system using facial recognition and provide insights into the application of this technology across different contexts.…”

Section: Literature Surveymentioning

confidence: 99%

Facial Recognition-Based Attendance Management System

2024

IRJMETS

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In today's educational and professional environments, the accurate and secure tracking of attendance is crucial, demanding systems that are efficient, adaptable, and punctual. This project proposes an innovative solution to this pressing challenge by leveraging facial recognition technology, specifically methods like LBPH (Local Binary Patterns Histogram) and Haar cascade, to introduce a robust "Facial Recognition Based Attendance Management System." This system represents a significant advancement in attendance monitoring, offering a user-friendly and dependable solution suitable for schools and businesses alike. The rapid evolution of biometric technologies, including techniques such as LBPH and Haar cascade, has revolutionized attendance monitoring and management for institutions and enterprises. Among various biometric approaches, facial recognition, employing algorithms like LBPH and Haar cascade, has emerged as a promising and non-intrusive method for achieving precise attendance tracking.In our comprehensive survey paper, we conduct an in-depth examination of the current state-of-the-art facial recognition-based attendance management systems, particularly those utilizing LBPH and Haar cascade algorithms. Our analysis explores multiple aspects of these systems, including underlying technologies, implementation challenges, advantages, and ethical considerations. This thorough investigation provides a wellrounded perspective on this rapidly evolving field.

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Section: Literature Surveymentioning

confidence: 99%

Facial Recognition-Based Attendance Management System

2024

IRJMETS

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“…In real world we use tit to unlock the phone and finding missing persons. Face detection can also be used for facial motion tracking, which is the process of deploying cameras or laser scanners to turn a human's face motions into a digital database [1]. Several algorithms have been reported in the literature reported in the domain of face recognition.…”

Section: Introductionmentioning

confidence: 99%

Attendance management system using face recognition

Jadhav,

Kamble,

Rathod

et al. 2024

IJ-AI

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<p>Traditional attendance systems consist of registers marked by teachers, leading to human error and a lot of maintenance. Time consumption is a key point in this system. We wanted to revolutionize the digital tools available in today's time i.e., facial recognition. This project has revolutionized to overcome the problems of the traditional system. Face recognition and marking the present is our project. A database of all students in the class is kept in single folder, and attendance is marked if each student's face matches with one of the stored faces. Otherwise, the face is ignored and not marked for attendance. In our project, face detection (machine learning) is used.</p>

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“…Here HOG is used for finding the faces and a deep learning model is used to recognize the face. [1]: This system focuses on automating attendance system by using HOG and neural network. It consists of four steps as finding all faces, posing and working faces, encoding faces and finding the person's name from the encodings.…”

Section: Introductionmentioning

confidence: 99%

Face Recognition Attendance Monitoring System

Dagade,

Janjire,

Jagdale

et al. 2023

IJRASET

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As we know attendance is the crucial part in colleges, schools, corporate offices etc. Attendance plays an important role for keeping track of student’s record. Mostly attendance is taken manually in most of the colleges and schools. The manual attendance process involves taking attendance by calling the name or by signing the attendance sheet. This manual process is very time consuming and it is difficult to maintain the attendance record. Due to this drawback of manual attendance system, there is a need of automated attendance system. Here facial recognition plays an important part for automated attendance system. This suggested study focuses on face detection algorithm to provide automated attendance system. This proposed system uses Histogram of Oriented Gradients (HOG) and Deep Convolutional Neural Network for face detection and face recognition respectively to build automated attendance system.

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Attendance Management System Using Facial Recognition

Cited by 6 publications

References 10 publications

Facial Recognition-Based Attendance Management System

Facial Recognition-Based Attendance Management System

Attendance management system using face recognition

Face Recognition Attendance Monitoring System

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