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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Anas Mohammad Quteishat
Al-Balqa Applied Univeristy
Computer Science & IT Engineering

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Facial emotion recognition through artificial ‎intelligence Anas Mohammad Quteishat; Mohammad Hassan; Ashraf Al Sharah; Ahmed Qtaishat
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 5: October 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i5.pp4700-4710

Abstract

This paper presents a fuzzy min-max deep neural network (FMMDNN) for facial emotion recognition (FER). ‎The fuzzy min-max neural network (FMMNN) will replace the classification layer in the convolutional neural network (CNN). The‎ fuzzy min-max (FMM) exhibits appealing features such as online adaptation, fast training, interpretability, and noise robustness. ‎The fully connected softmax layer in the CNN is replaced by the FMMNN, where hyperboxes will ‎be created and used for classification purposes. The FER2013 dataset is used ‎to test the performance of the proposed method. The empirical results show that adding an FMMNN ‎layer to the CNN network improves the performance.
Co-Authors Ahmed Qtaishat Ashraf Al Sharah Mohammad Hassan