Cross-domain transferable discriminant dictionary based sparse representation approach for EEG emotion-level recognition-Reference-Cited by-同舟云学术

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Cross-domain transferable discriminant dictionary based sparse representation approach for EEG emotion-level recognition

Published:2023-09-08 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Ni Tongguang,He Chengbing,Jiang Yizhang,Gu Xiaoqing^ORCID

Funder

Natural Science Foundation of Jiangsu Province

Future Network Scientific Research Fund Project

open project form Jiangsu Key Laboratory of Media Design and Software Technology

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-023-01957-9.pdf

Reference29 articles.

1. Feller S, Castillo E, Greenberg J et al (2018) University of California Los Angeles Community Translational Science Team, emotional well-being and public health: Proposal for a model national initiative. Public Health Rep 133(2):136–141

2. Wu M, Teng W, Fan C et al (2023) An investigation of olfactory-enhanced video on EEG-based emotion recognition. IEEE Trans Neural Syst Rehabil Eng 31(3):1602–1613

3. Kong W, Song X, Sun J (2021) Emotion recognition based on sparse representation of phase synchronization features. Multimed Tools Appl 80:21203–21217

4. Liu S, Wang Z, An Y et al (2023) EEG emotion recognition based on the attention mechanism and pre-trained convolution capsule network. Knowl-Based Syst 265(4):110372

5. Canamero L (2021) Embodied robot models for interdisciplinary emotion research. IEEE Trans Affect Comput 12(2):340–351

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