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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 05

Published on: May 2026

SMART ATTENDANCE SYSTEM USING ARTIFICIAL INTELLIGENCE BASED FACE RECOGNITION

Shoaib Akhtar Mo Ariz Nazish Junaid Nehal Wahab

Yusra Beg

Department of Computer Science and Engineering Integral University Lucknow

Uttar Pradesh India
DOI:https://doi.org/10.55041/ijcope.v2i5.284

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

This paper presents a comprehensive smart attendance system based on artificial intelligence and face recognition technology. Traditional attendance methods are inefficient, time-consuming, and prone to proxy attendance. The proposed system utilizes deep learningbased facial recognition to automate attendance marking in real time. The system integrates face detection, feature extraction, and identity verification modules to ensure accurate recognition. Experimental analysis demonstrates improved efficiency, scalability, and reliability compared to traditional systems. The proposed approach offers a contactless, secure, and intelligent solution for modern educational environments.

Keywords— Artificial Intelligence, Face Recognition, Deep Learning, Attendance System

How to Cite this Paper

Akhtar, S., Ariz, M., Junaid, N. & Wahab, N. (2026). Smart Attendance System Using Artificial Intelligence Based Face Recognition. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.284

Akhtar, Shoaib, et al.. "Smart Attendance System Using Artificial Intelligence Based Face Recognition." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.284.

Akhtar, Shoaib,Mo Ariz,Nazish Junaid, and Nehal Wahab. "Smart Attendance System Using Artificial Intelligence Based Face Recognition." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.284.

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References


  1. Turk and A. Pentland, “Eigenfaces for Recognition,” Journal of Cognitive Neuroscience, 1991.

  2. Viola and M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features,” CVPR, 2001.

  3. Schroff, D. Kalenichenko, and J. Philbin,

  4. Lowe, “Distinctive Image Features from Scale“FaceNet: A Unified Embedding for Face Recog- Invariant Keypoints,” IJCV, 2004. nition and Clustering,” CVPR, 2015.

  5. T. Ahonen et al., “Face Recognition with Local Bi[4] Y. Taigman et al., “DeepFace: Closing the Gap nary Patterns,” ECCV, 2006. to Human-Level Performance in Face Verification,”

  6. CVPR, 2014A. Georghiades et al., “From Few to Many: Illumi-nation Cone Models for Face Recognition,” IEEE,

  7. Goodfellow et al., “Deep Learning,” MIT Press, 2001.2016.

  8. Zhao et al., “Face Recognition: A Literature Survey,” ACM Computing Surveys, 2003.

  9. Brunelli, “Face Recognition: Features versus Templates,” IEEE Transactions, 2002.

  10. Krizhevsky et al., “ImageNet Classification with Deep Convolutional Neural Networks,” NIPS, 2012.

  11. Deng et al., “ArcFace: Additive Angular Margin Loss for Deep Face Recognition,” CVPR, 2019.

  12. Guo and N. Zhang, “A Survey on Deep Learning Based Face Recognition,” Computer Vision and Image Understanding, 2019.

Ethical Compliance & Review Process

  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
  • •Authors retain copyright.
  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: May 10 2026
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