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  • 标题:Analysis of student sentiment during video class with multi-layer deep learning approach
  • 本地全文:下载
  • 作者:Imrus Salehin ; Nazmun Nessa Moon ; Iftakhar Mohammad Talha
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2022
  • 卷号:12
  • 期号:4
  • 页码:3981-3993
  • DOI:10.11591/ijece.v12i4.pp3981-3993
  • 语种:English
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:The modern education system is an essential part of the rise of technology. The E-learning education system is not just an experimental system; it is a vital learning system for the whole world over the last few months. In our research, we have developed our learning method in a more effective and modern way for students and teachers. For significant implementation, we are implementing convolutions neural networks and advanced data classifiers. The expression and mood analysis of a student during the onlineclass is the main focus of our study. For output measure, we divide the final output result as attentive, inattentive, understand, and neutral. Showing the output in real-time online class and for sensory analysis, we have used support vector machine (SVM) and OpenCV. The level of 5*4 neural network is created for this work. An advanced learning medium is proposed through our study. Teachers can monitor the live class and different feelings of a student during the class period through this system.
  • 关键词:Convolutional neural network;Deep learning;Electronic-learning;Image data;Sentiment analysis
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