Self-supervised group meiosis contrastive learning for EEG-based emotion recognition-Reference-Cited by-同舟云学术

Self-supervised group meiosis contrastive learning for EEG-based emotion recognition

Published:2023-09-05 Issue:22 Volume:53 Page:27207-27225
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Kan Haoning,Yu Jiale,Huang Jiajin,Liu Zihe,Wang Heqian,Zhou Haiyan

Funder

Beijing Natural Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-023-04971-0.pdf

Reference54 articles.

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3. Subasi A, Tuncer T, Dogan S et al (2021) EEG-based emotion recognition using tunable q wavelet transform and rotation forest ensemble classifier. Biomed Signal Process Control 68(102):648

4. Tuncer T, Dogan S, Baygin M et al (2021) Tetromino pattern based accurate EEG emotion classification model. Artif Intell Med 123(102):210

5. Dogan A, Barua PD, Baygin M et al (2022) (2022) Automated accurate emotion classification using clefia pattern-based features with EEG signals. Int J Healthc Manag. https://doi.org/10.1080/20479700.2022.2141694

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1. Emotion Recognition based on Physiological Signals Multi-head Attention Contrastive Learning;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

2. Applications of Self-Supervised Learning to Biomedical Signals: A Survey;IEEE Access;2023