Improving Cross-Subject Emotion Recognition Performance with an Encoder-Decoder Structure

Emotion recognition based on EEG is an important task in the field of affective computing. Due to individual differences, emotion recognition performance of cross-subject models is significantly lower than that of subject-dependent models. To minimize the degradation of emotion recognition performan...

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Veröffentlicht in:	2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Jg. 2024; S. 1 - 4
Hauptverfasser:	Cui, Haowei, Shi, Hanwen, Lu, Bao-Liang, Zheng, Wei-Long
Format:	Tagungsbericht Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.07.2024
Schlagworte:	Adaptation models Algorithms Brain modeling Computational modeling Convolution Degradation Electroencephalography Electroencephalography - methods Emotion recognition Emotions - physiology Engineering in medicine and biology Entropy Humans Signal Processing, Computer-Assisted Training
ISSN:	2694-0604, 2694-0604
Online-Zugang:	Volltext
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