A Supervised Information Enhanced Multi-Granularity Contrastive Learning Framework for EEG Based Emotion Recognition
Author:
Affiliation:
1. Qilu University of Technology (Shandong Academy of Sciences),Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China
2. Beijing Institute of Technology,Institute of Engineering Medicine,Beijing,China
Funder
Ministry of Science and Technology
Shandong Academy of Sciences
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10445798/10445803/10447740.pdf?arnumber=10447740
Reference18 articles.
1. Latent Factor Decoding of Multi-Channel EEG for Emotion Recognition Through Autoencoder-Like Neural Networks
2. Long-range correlation analysis of high frequency prefrontal electroencephalogram oscillations for dynamic emotion recognition
3. EEG Based Emotion Recognition: A Tutorial and Review
4. TS2Vec: Towards Universal Representation of Time Series
5. MEG and EEG data analysis with MNE-Python
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