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  Published Paper Details:

  Paper Title

IMPLEMENTATION OF ATTENDANCE SYSTEM USING FACE RECOGNITION AND MACHINE LEARNING

  Authors

  Sonali Appasaheb Patil,  Avdhoot Ashok Gaikwad,  Chetana Pramod Baviskar,  Shrawani Rajesh Bartakke,  Shubham Sanjay Kulkarni

  Keywords

Face Recognition, Machine Learning, Attendance, Biometric, Python, PCA, OpenCV, training, testing, Haar Cascade.

  Abstract


The prototype of an automated Online Biometric-enabled Class Attendance Register System is shown in this study (OBCARS). In higher education courses, the technology is being planned and developed to address the problem of lost and/or shredded attendance record paper sheets. The system also aims to provide a dependable and effective class attendance tracking system that avoids students imitating attendance markers and simplifies the calculation of students' attendance records. Biometric appreciation includes both pragmatic biometric behavior in contrast to previously poised data for a focus and an open-mindedness of computation. Because of differences in biological traits and actions both within and among persons, estimated identical is required. It uses a student's attendance in class to determine their attendance. The student's face will be identified by the technology and save the response to the database automatically.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2205328

  Paper ID - 219776

  Page Number(s) - c890-c895

  Pubished in - Volume 10 | Issue 5 | May 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Sonali Appasaheb Patil,  Avdhoot Ashok Gaikwad,  Chetana Pramod Baviskar,  Shrawani Rajesh Bartakke,  Shubham Sanjay Kulkarni,   "IMPLEMENTATION OF ATTENDANCE SYSTEM USING FACE RECOGNITION AND MACHINE LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 5, pp.c890-c895, May 2022, Available at :http://www.ijcrt.org/papers/IJCRT2205328.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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