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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM18751
Volume:
7 |
4 |
Apr 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The most widely used and popular technology nowadays is face recognition. It works well to provide machine vision so that it can interact with people more effectively. If machines can read our faces, then our form of life will reflect that. The world will enter a new dimension according to face recognition technology. Finding identity and security will be advantageous in many ways. The identification and verification of a person using their facial features are done by a facial recognition attendance system, which also uses technology to automatically mark attendance. The software can be utilized by a variety of users, including employees, students, and others. Real-time data collection and data storage is done by the system. In this article, we describe a face-recognition smart library system that does away with the majority of the difficult things that traditional library management systems require. A real-time attendance system based on human face recognition and basic algorithms is the library management system. Before, each library user’s login and logout details were manually entered into records (books). By keeping books, there is a chance of data loss, and multiple records might be challenging to keep up with. Given this, we are putting up a clever method for maintaining faculty/student login and logout library information using CNN, or Convolution Neural Networks, a type of Deep Learning technology based on face recognition.
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Publication Date
4/24/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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