基于人工智能的实时人脸识别考勤系统的比较研究

P. Pattnaik, Kalyan Kumar Mohanty
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引用次数: 8

摘要

面部识别是生物识别系统的一个强大工具,它可以从图像和视频中获取数据。自动考勤系统可以代替传统的考勤系统,更有效地利用课堂时间。在本文中,实时考勤监控使用了一个web应用程序,该应用程序可以通过使用本地服务器和亚马逊网络服务(AWS)云识别应用程序编程接口(API)远程操作。第一种方法包括五个部分:人脸检测、预处理、培训和人脸识别,通过这些部分,考勤将被记录并邮寄给相应的老师。第二种方法是基于AWS识别API,该API在云中处理数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI-Based Techniques for Real-Time Face Recognition-based Attendance System- A comparative Study
Face recognition is a powerful tool for a biometric system that takes data from both images and videos. The traditional attendance system can be replaced by the automatic attendance system to utilize class time more effectively. In this paper real-time, attendance monitoring uses a web app that can be operated remotely by using a local server and Amazon Web Service (AWS) cloud recognition Application Programming Interface (API). The first approach follows five sections which are face detection, preprocessing, training and, face recognition through which attendance will be recorded and mailed to the respective teacher. The second approach is based on AWS recognition API which processes the data in the cloud.
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