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  • 标题:Development and Analysis of a Machine Learning Based Software for Assisting Online Classes during COVID-19
  • 本地全文:下载
  • 作者:Tasfiqul Ghani ; Nusrat Jahan ; Mohammad Monirujjaman Khan
  • 期刊名称:Journal of Software Engineering and Applications
  • 印刷版ISSN:1945-3116
  • 电子版ISSN:1945-3124
  • 出版年度:2021
  • 卷号:14
  • 期号:3
  • 页码:83-94
  • DOI:10.4236/jsea.2021.143006
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:Amid the Covid-19 widespread, it has been challenging for educational institutions to conduct online classes, facing multiples challenges. This paper provides an insight into different approaches in facing those challenges which includes conducting a fair online class for students. It is tough for an instructor to keep track of their students at the same time because it is difficult to screen if any of the understudies within the class are not present, mindful, or drowsing. This paper discusses a possible solution, something new that can offer support to instructors seeing things from a more significant point of view. The solution is a facial analysis computer program that can let instructors know which students are attentive and who is not. There’s a green and red square box for face detection, for which Instructors can watch by seeing a green box on those mindful students conjointly, a red box on those who are not mindful at all. This paper finds that the program can automatically give attendance by analyzing data from face detection. It has other features for which the teacher can also know if any student leaves the class early. In this paper, model design, performance analysis, and online class assistant aspects of the program have been discussed.
  • 关键词:Online Class;Python;Technology;Artificial Intelligence;Analysis;Machine Learning;Covid-19;Software;Face Detection;Drowsiness Detector
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