Multi-Modal Domain Adaptation Variational Auto-encoder for EEG-Based Emotion Recognition

Traditional electroencephalograph(EEG)-based emo-tion recognition requires a large number of calibration samples to build a model for a specific subject,which restricts the application of the affective brain computer interface(BCI)in practice.We attempt to use the multi-modal data from the past sess...

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Vydané v:	自动化学报（英文版） Ročník 9; číslo 9; s. 1612 - 1626
Hlavní autori:	Yixin Wang, Shuang Qiu, Dan Li, Changde Du, Bao-Liang Lu, Huiguang He
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Research Center for Brain-inspired Intelligence,National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Science,Beijing 100190 01.09.2022 University of Chinese Academy of Sciences,Beijing 100049%Research Center for Brain-inspired Intelligence,National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Science,Beijing 100190 Beijing Institute of Control and Electronic Technology,Beijing 100038,China%Research Center for Brain-inspired Intelligence,National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Science,Beijing 100190 Center for Excellence in Brain Science and Intelligence Technology,Chinese Academy of Science,Beijing,China University of Chinese Academy of Sciences,Beijing 100049 School of Mathematics and Information Sciences,Yantai University,Yantai 264003,China%Department of Computer Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China%Research Center for Brain-inspired Intelligence,National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Science,Beijing 100190
Predmet:	Cycle-consistency multi modality electroence-phalograph(EEG) domain adaptation variational autoencoder
ISSN:	2329-9266
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