Abstract
Learning management systems (LMSs) have integrated multiple technologies to enhance the e-learning experience. One such technology is the emotional recognition system (ERS), which provides tutors with data on learners' emotions, including anger, sadness, happiness, and more. ERS utilizes various data sources like facial expressions, body activities, and brain signals to recognize emotions. This paper provides an overview of the ERS structure and discusses the state-of-the-art technologies in this field. The results indicate that deep learning based ERS using VGG19 for feature extraction over the FER2013 dataset is reliable with a recognition accuracy of 87% using Random Forest Algorithm
Recommended Citation
Subhi, Mohammed Ahmed; Hussein, Mohammed Khaleel; Ali, Ali Abdullah; and Mohammed, Saleh Mahdi
(2024)
"LEARNERS' EMOTIONS ESTIMATION USING VIDEO PROCESSING TECHNIQUES FOR OPTIMUM E-LEARNING EXPERIENCE,"
Iraqi Journal for Computer Science and Mathematics: Vol. 5:
Iss.
3, Article 33.
DOI: https://doi.org/10.52866/ijcsm.2024.05.03.038
Available at:
https://ijcsm.researchcommons.org/ijcsm/vol5/iss3/33
