Optimization The Utility Of E-Learning Platform Through Integrating Smart Emotional Recognition Feature

Authors

  • Layth Mohammed Abbas Al- Mashhadani Al-Farabi University College, Dept. of Computer Engineering, Baghdad, Iraq
  • Isam Abdulmunem Alobaidi Al-Farabi University College, Dept. of Computer Engineering, Baghdad, Iraq
  • Alaa Mohammed Abbas Al- Mashhadani Al-Farabi University College, Dept. of Computer Engineering, Baghdad, Iraq

DOI:

https://doi.org/10.59746/jfes.v1i2.42

Keywords:

Classrooms, LMS, E-learning, Voice, Features, Classification

Abstract

Educational applications of image processing have emerged due to data collection tools development. Education is vital field in human life where highly accurate performance is required. Integrating image processing and deep learning with the education will help to optimize the performance of entire system. It is possible now to make out the student’s emotional status through study the features from facial images taken for a group of students. That reduces the time and cost of the education by providing a facility similar to the regular classrooms environments.  Which may help plenty of people who are unable to access regular educational facilities due to intolerable cost. In this paper, automatic emotional detection is being performed using neural network. Two models are used namely artificial neural network and CNN neural network. The models are tested using emotional images data. Results are reported 96.7 % and 99.2 % accuracies from bother artificial neural network and CNN respectively.

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Published

2022-12-01

Issue

Vol. 1 No. 2 (2022): Journal of Al-Farabi For Engineering Sciences

Section

Articles