Four class emotion classifcation in virtual reality using pupillometry
Background: Emotion classifcation remains a challenging problem in afective computing. The large majority of emotion classifcation studies rely on electroencephalography (EEG) and/or electrocardiography (ECG) signals and only classifes the emotions into two or three classes. Moreover, the stimuli us...
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Main Authors: | Lim, Jia Zheng, James Mountstephens, Jason Teo |
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Format: | Article |
Language: | English English |
Published: |
2020
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Online Access: | https://eprints.ums.edu.my/id/eprint/25955/1/Four%20class%20emotion%20classifcation%20in%20virtual%20reality%20using%20pupillometry.pdf https://eprints.ums.edu.my/id/eprint/25955/2/Four%20class%20emotion%20classifcation%20in%20virtual%20reality%20using%20pupillometry1.pdf https://eprints.ums.edu.my/id/eprint/25955/ https://doi.org/10.1186/s40537-020-00322-9 |
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