Facial expression recognition using CNN for healthcare

CHRISMORGAN SHINTARO; WILLIAM; FELIX NOVANDO; AZANI CEMPAKA SARI

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Facial expression recognition using CNN for healthcare

Author(s)

CHRISMORGAN SHINTARO School of Computer Science, Department of Bina Nusantara University, Jakarta, Indonesia

WILLIAM School of Computer Science, Department of Bina Nusantara University, Jakarta, Indonesia

FELIX NOVANDO School of Computer Science, Department of Bina Nusantara University, Jakarta, Indonesia

AZANI CEMPAKA SARI School of Computer Science, Department of Bina Nusantara University, Jakarta, Indonesia

Abstract

Human emotion is the way how human express anything from themselves. We can extract many informations from a human emotion alone like temper and health condition. Due to in Indonesia, people usually don't visit doctor just to seeing their own face condition. We can use a computer vision task to do so. This paper is aim to train a computer vision model that can recognize a human face emotion. Inspired by Convolutional Neural Networks (CNNs) that capable of doing image classification, we proposed our own designed multiple CNN classification model with different layer settings to do facial expression recognition. Next we applied the model on the FER2013 dataset. The best training accuracy achieved by the second model in 92.40% accuracy and the best validation accuracy achieved by third model in 67.43% accuracy.

Publication Details

Page(s) 1227-1235

DOI DOI not available

Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 5, Year: 2022

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Keywords

Classification, Health, Computer vision, CNN, Facial expression recognition

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