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Instance-Adaptive Graph for EEG Emotion Recognition
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
To tackle the individual differences and characterize the dynamic relationships among different EEG regions for EEG emotion recognition, in this paper, we propose a novel instance-adaptive graph method (IAG), which employs a more flexible way to construct graphic connections so as to present different graphic representations determined by different input instances. To fit the different EEG pattern, we employ an additional branch to characterize the intrinsic dynamic relationships betweendoi:10.1609/aaai.v34i03.5656 fatcat:xgvqsaroh5fmzjn46ma3asmwda