Abstract
Face recognition technology using AI has seen paradigm shift in the evolving world. Automatic attendance monitoring using real-time face identification is a solution to handle attendance in any small/large as well as scalable organization. Traditional methods in the organization involve calling names or signing sheets with individuals, which is a very time-consuming process and provides insurance. This is also subjected to manual errors. Automation of attendance recording and monitoring through face recognition is a process of identifying the face for taking attendance by using the image of the human face as biometric parameter captured through a surveillance camera in the premise. This article presents an effective way of attendance monitoring by making use of deep learning technology and compares its results with the state-of-the-art approaches.
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Srivastava, A.K., Mishra, C., Mishra, A., Srivastava, A. (2024). Towards Intelligent Attendance Monitoring for Scalable Organization with Hybrid Model Using Deep Learning. In: Chaturvedi, A., Hasan, S.U., Roy, B.K., Tsaban, B. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2023. Lecture Notes in Networks and Systems, vol 918. Springer, Singapore. https://doi.org/10.1007/978-981-97-0641-9_39
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DOI: https://doi.org/10.1007/978-981-97-0641-9_39
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