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Analysis of Student Sentiment During Video Class with Multilayer Deep Learning Approach

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dc.contributor.author Salehin, Imrus
dc.contributor.author Moon, Nazmun Nessa
dc.contributor.author Talha, Iftakhar Mohammad
dc.contributor.author Hasan, Md. Mehedi
dc.contributor.author Nur, Farnaz Narin
dc.contributor.author Hakim, Md. Azizul
dc.contributor.author Haque, Farhan Al
dc.date.accessioned 2024-02-13T08:25:39Z
dc.date.available 2024-02-13T08:25:39Z
dc.date.issued 2022-08-08
dc.identifier.issn 2088-8708
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/11424
dc.description.abstract 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. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Technology en_US
dc.subject Education system en_US
dc.subject E-Learning Education System en_US
dc.subject Neural Networks en_US
dc.title Analysis of Student Sentiment During Video Class with Multilayer Deep Learning Approach en_US
dc.type Article en_US


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