Deep learning approaches for facial expression recognition
International Journal of Development Research
Deep learning approaches for facial expression recognition
Received 10th October, 2021; Received in revised form 08th November, 2021; Accepted 27th December, 2021; Published online 30th January, 2022
Copyright © 2022, Felipe da Silva Braz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Recent studies point to the increasing importance of facial expression recognition (FER) in different application areas like healthcare and assistive technologies. Among these, computational diagnosis and evaluation of mental or facial diseases, machine-assisted rehabilitation, clinical psychology and psychiatry, pain monitoring, can be highlighted. FER also plays a relevant role in the case of diagnosis or assessment of cognitive impairments, such as autism and schizophrenia. The literature shows that FER systems effectively working in a health setting is still an open research problem. This paper presents a study on techniques for FER based on images, applying deep learning algorithms. A comparative analysis is performed, pointing out the combinations of algorithms and repositories that manage to obtain gains in the accuracy index.
