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Deep Learning based Emotion Classification with Temporal Pupillometry Sequences

Kanwal

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Abstract

In the recent era, automatic systems are the necessity of science. Systems for recognizing human emotions have gained popularity in various areas of knowledge specifically psychologists and psycho-physiologists. The interaction of the human-computer using physiological signals is the precise parameter for the recognition of emotion. However, pupillometry was used in this study as an unintentional direct brain response to capture human emotions using in-depth learning. Deep learning concepts using LSTM (Long Short Term Memory) were used in this study to classify emotions. Time series data for two emotions i.e. disgust and fear were used after the pre-treatment phase and subsequently proposed a classifier for the recognition of emotions.

Conference Name 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)
Conference Location Cape Town, South Africa
Start Date Dec 9, 2021
End Date Dec 10, 2021
Acceptance Date Dec 9, 2021
Publication Date Dec 9, 2021
Series Title 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)
Publisher URL https://ieeexplore.ieee.org/document/9698663

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