SFT-SGAT: A semi-supervised fine-tuning self-supervised graph attention network for emotion recognition and consciousness detection-Reference-Cited by-同舟云学术

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SFT-SGAT: A semi-supervised fine-tuning self-supervised graph attention network for emotion recognition and consciousness detection

Published:2024-12 Issue: Volume:180 Page:106643
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Qiu Lina^ORCID,Zhong Liangquan^ORCID,Li Jianping^ORCID,Feng Weisen^ORCID,Zhou Chengju,Pan Jiahui^ORCID

Publisher

Elsevier BV

Reference53 articles.

1. Differential lateralization for positive and negative emotion in the human brain: EEG spectral analysis;Ahern;Neuropsychologia,1985

2. Deconstructing the “resting” state: exploring the temporal dynamics of frontal alpha asymmetry as an endophenotype for depression;Allen;Frontiers in Human Neuroscience,2010

3. Consciousness and emotional facial expression recognition: Subliminal/supraliminal stimulation effect on N200 and P300 ERPs;Balconi;Journal of Psychophysiology,2007

4. Calibration free meta learning based approach for subject independent EEG emotion recognition;Bhosale;Biomedical Signal Processing and Control,2022

5. Meta-analysis of emotion recognition deficits in major depressive disorder;Dalili;Psychological Medicine,2015

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