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The incorporation of facial recognition technology into attendance tracking systems in modern educational settings offers a significant opportunity to improve efficiency and accountability. This paper examines the deployment of facial recognition systems utilizing sophisticated deep learning algorithms like DeepFace and FaceNet, which provide exceptional precision while demanding little hardware resources. The system showcases substantial advancements in the areas of real-time monitoring, user interface design, and data processing efficiency. Through the implementation of empirical tests and a comparative analysis of current solutions, we offer valuable insights into the efficiency and practicality of this technology, therefore facilitating future progress in educational technology and administrative procedures.

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Advancing Attendance Monitoring: A Machine Learning-Driven Approach Through Facial Recognition Line

  • 会议论文

  • 发表日期：

    2025年

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  • Shreya Agrawal,
  • Ayush Shekhar,
  • Madhu Shukla,
  • Neel H. Dholakia,
  • Vipul Ladva

摘要

The incorporation of facial recognition technology into attendance tracking systems in modern educational settings offers a significant opportunity to improve efficiency and accountability. This paper examines the deployment of facial recognition systems utilizing sophisticated deep learning algorithms like DeepFace and FaceNet, which provide exceptional precision while demanding little hardware resources. The system showcases substantial advancements in the areas of real-time monitoring, user interface design, and data processing efficiency. Through the implementation of empirical tests and a comparative analysis of current solutions, we offer valuable insights into the efficiency and practicality of this technology, therefore facilitating future progress in educational technology and administrative procedures.