Comparative analysis of facial recognition models using video for real time attendance monitoring system

Patil, Payal; Shinde, Swati

doi:10.1109/iceca49313.2020.9297374

Cited by 11 publications

(8 citation statements)

References 7 publications

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“…The application detected and recognized students in the class with a maximum accuracy of 92%. [32] An automatic attendance management system was realized based on face detection and face recognition methods under Haar's Cascade method and CNN algorithm. They compared three face detection methods, of which the Viola-Jones method obtained the highest accuracy (87.71%).…”

Section: Review Resultsmentioning

confidence: 99%

“…Related studies Prevent impersonation and false assistance [21], [22], [27], [28], [30], [31], [32], [34], [35], [38], [39], [40], [41] Saving time and work for teachers and students [21], [23], [33], [34], [37], [38], [41], [43] Increasing the security and reliability of data [21], [24], [25], [26], [27], [28], [29], [35], [36], [37], [38], [42] Increases productivity [23] Improving work culture, accountability, and transparency [23], [40], [41], [43] Generates a clear audit trail for attendance records [23] Biometric traits do not change or are difficult to alter over time.…”

Section: Benefitsmentioning

confidence: 99%

See 1 more Smart Citation

Systematic Literature Review: Biometric Technology Applied to Educational Institutions

Necochea-Chamorro,

Sotelo Asalde,

Loli Nuñez

et al. 2024

TEM Journal

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Biometric technology, founded on recognizing distinctive individual features, enhances identification and automation, yielding personal and institutional benefits. This literature review employs the Kitchenham and Charters methodology to analyze recent perspectives on biometric technology in educational time and attendance. The analysis identifies benefits, such as preventing impersonation and enhancing data security, but emphasizes concerns about biometric alterations and hardware/software failures hindering optimal outcomes. A noteworthy trend is adopting a bimodal behavioral approach in biometric technologies in education. The study recommends research avenues focusing on privacy safeguards, biometric system robustness, and technological resilience. Beyond mere identification, a shift towards quantitative and descriptive methods is proposed, guiding future research. The results underscore the importance of a multimodal approach and stringent security measures to address biometric system vulnerabilities. Future exploration should consider integrating emerging technologies to enhance system resilience and data protection, providing a comprehensive guide for refining and expanding biometric technology applications in education.

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Section: Review Resultsmentioning

confidence: 99%

Section: Benefitsmentioning

confidence: 99%

Systematic Literature Review: Biometric Technology Applied to Educational Institutions

Necochea-Chamorro,

Sotelo Asalde,

Loli Nuñez

et al. 2024

TEM Journal

View full text Add to dashboard Cite

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“…CNN algor ithm is a machine lear ning method f or manipulation of 2-D objects drawback of the system that . One uses this algorithm is the database was too large as they had 60 images per student for training the model [2]. Thus, this algorithm is not robust for large datasets [3].…”

Section: Discussionmentioning

confidence: 99%

“…A device was built that utilized a modified Haar cascade algorithm for human face detection, and a CNN algorithm is used for recognition [2] and got 94.6% accuracy on a realtime database for the attendance system.…”

Section: Literature Reviewmentioning

confidence: 99%

A Systematic Review of Attendance Systems Based on Face Recognition

Modak

Shah

Surana

et al. 2022

PIJR

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In this digital era, face recognition system plays a vital role in almost every sector. Face recognition is one of the most implemented biometrics across various different fields. Classroom attendance check is a contributing factor to student participation and the final success in the courses. Every institute follows their own way for taking attendance.Some are taking attendance manually using papers or a register file or different biometric techniques. Taking attendance by calling out names or passing around an attendance sheet is time-consuming, and the latter is open to easy fraud.In this paper, the comparative analysis of various existing approaches on attendance management system based on facial recognition that are used to monitor attendance in various institutions using Fingerprint,GPS,RFID etc.is discussed with their limitations.

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“…By using java, the appearance of the program to be made can be easily determined. Because in this attendance system [31][32][33][34][35], there is student attendance data that will be displayed on a website page, java is used.…”

Section: Overview Of Attendance Data Processing System Using Fingerprintmentioning

confidence: 99%

Implementation of Fingerprint Sensors for Fingerprint Reader Prototypes Using a Microcontroller

Siregar¹,

Siagian

2022

IOTA

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study aims to create a Fingerprint Sensor Implementation System for a Fingerprint Reader Prototype Using a Microcontroller. Implementing the Fingerprint Sensor for the Fingerprint Reader Prototype is run by an application connected by a USB cable. The Fingerprint Sensor Implementation System for the Fingerprint Reader Prototype is made for fast and more accurate attendance and cannot be manipulated. The Fingerprint Sensor Implementation System for the Fingerprint Reader Prototype is the problem. Namely, the attendance problem, which is still manual using books; after that, the design and manufacture of the Fingerprint Reader prototype using a Microcontroller or applications through NetBeans. Then implementation and testing. Then at the trial stage, the Arduino application was carried out. The result of this study is the Fingerprint Sensor Implementation System for the Prototype Fingerprint Reader Using a Microcontroller and development in the Internet of Things.

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Comparative analysis of facial recognition models using video for real time attendance monitoring system

Cited by 11 publications

References 7 publications

Systematic Literature Review: Biometric Technology Applied to Educational Institutions

Systematic Literature Review: Biometric Technology Applied to Educational Institutions

A Systematic Review of Attendance Systems Based on Face Recognition

Implementation of Fingerprint Sensors for Fingerprint Reader Prototypes Using a Microcontroller

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