Smart attendance using deep learning and computer vision

被引:5
|
作者
Seelam, Vivek [1 ]
Penugonda, Akhil Kumar [1 ]
Kalyan, B. Pavan [1 ]
Priya, M. Bindu [1 ]
Prakash, M. Durga [1 ]
机构
[1] Velagapudi Ramakrishna Siddhartha Engn Coll, Dept Elect & Commun Engn, Vijayawada 520007, Andhra Pradesh, India
关键词
Convolutional Neural networks; Deep learning; Facenet; Haar cascades; Raspberry Pi; Smart classroom;
D O I
10.1016/j.matpr.2021.02.625
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Attendance is an essential part of daily classroom evaluation. Traditional classroom follows a manual attendance marking system, i.e., calling a student's names or by forwarding an attendance sheet. This process is both time-consuming and error-prone, i.e., student proxy, etc. Hence a face recognition based smart classroom attendance management system using computer vision and deep learning implemented on a Raspberry Pi has been proposed. It has been proposed to mount a camera at the top of the blackboard so that the students are visible while they are sitting down. A face detection algorithm followed by face recognition has been used to mark the attendance of the detected student. (c) 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Materials, Manufacturing and Mechanical Engineering for Sustainable Developments-2020.
引用
收藏
页码:4091 / 4094
页数:4
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