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e3sconf_icies2022_01032.pdf (453.35 kB)

Using Deep Learning to detect Facial Expression from front camera: Towards students’ interactions analyze

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journal contribution
submitted on 2024-04-03, 08:53 and posted on 2024-04-24, 05:42 authored by N. El Bahri, Z. Itahriouan, S. Brahim Belhaouari, A. Abtoy

The recent advancement of Artificial Intelligence (AI) affords ambition to exploit this revolution in multiple fields. Computer-assisted teaching and learning creates a very important area of AI application. Consequently, this last will be able to revolutionize this field. In research conducted by our laboratory, we are interested to explore AI trends to teaching and learning technologies. As part of this, we aim to study learner’s behaviors in education and learning environment, thus we aim to analyze the student through the front camera, as a first step we intend to develop a model that classify face’s images based on deep learning and Convolutional Neural Networks (CNN) in particular. Model development of images classification can be realized based in several technologies, we have chosen for this study to use IBM solutions, which are provided on the cloud. This paper describes the training experiment and the model development based on two alternatives proposed by IBM where the goal is to generate the most precise model. It presents a comparative study between the two approaches and ends with result discussing and the choice of the accurate solution for deployment in our teaching and learning system.

Other Information

Published in: E3S Web of Conferences
See article on publisher's website:



  • English


EDP Sciences

Publication Year

  • 2022

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU