OGSSL: A Semi-Supervised Classification Model Coupled With Optimal Graph Learning for EEG Emotion Recognition

OGSSL: A Semi-Supervised Classification Model Coupled With Optimal Graph Learning for EEG Emotion Recognition

Electroencephalogram(EEG) signals are generated from central nervous system which are difficult to disguise, leading to its popularity in emotion recognition. Recently,semi-supervisedlearning exhibits promisingemotion recognition performance by involving unlabeled EEG data into model training. Howev...

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Bibliographic Details
Main Authors: Yong Peng, Fengzhe Jin, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Electroencephalogram (EEG)
emotion recognition
feature selection
graph learning
semi-supervised learning
Online Access:https://ieeexplore.ieee.org/document/9775684/

Internet

https://ieeexplore.ieee.org/document/9775684/

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