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| 한글제목(Korean Title) |
그래프 컨볼루션 신경망을 이용한 정량화 뇌파 기반 감정 인식 |
| 영문제목(English Title) |
Quantitative EEG based Emotion Recognition Using Graph Convolutional Neural Network |
| 저자(Author) |
김대현
최영석
Dae-Hyeon Kim
Young-Seok Choi
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| 원문수록처(Citation) |
VOL 45 NO. 01 PP. 1577 ~ 1580 (2022. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
With the recent advent of human-machine interaction, emotion recognition using electroencephalogram (EEG) has gathered significant attention in affective computing. Considering the characteristic of EEG signals, various graph neural networks have been applied in emotion recognition. In this work, we propose an effective EEG feature and a spectral graph convolutional neural network using dynamical update (SGCN-DU) which can consider the functional correlation between EEG feature pairs. The result using the SJTU emotion EEG dataset (SEED) showed that the emotion recognition performance of the proposed model is higher than the traditional method. |
| 키워드(Keyword) |
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| 파일첨부 |
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