.png){kind=icon}
返回
GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition
.png){kind=icon}
OA
AI
DOI：10.1109/TAFFC.2022.3170428.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Previous electroencephalogram (EEG) emotion recognition relies on single-task learning, which may lead to overfitting and learned emotion features lacking generalization. In this paper, a graph-based multi-task self-supervised learning model (GMSS) for EEG emotion recognition is proposed. GMSS has the ability to learn more general representations by integrating multiple self-supervised tasks, including spatial and frequency jigsaw puzzle tasks, and contrastive learning tasks. By learning from multiple tasks simultaneously, GMSS can find a representation that captures all of the tasks thereby decreasing the chance of overfitting on the original task, i.e., emotion recognition task. In particular, the spatial jigsaw puzzle task aims to capture the intrinsic spatial relationships of different brain regions. Considering the importance of frequency information in EEG emotional signals, the goal of the frequency jigsaw puzzle task is to explore the crucial frequency bands for EEG emotion recognition. To further regularize the learned features and encourage the network to learn inherent representations, contrastive learning task is adopted in this work by mapping the transformed data into a common feature space. The performance of the proposed GMSS is compared with several popular unsupervised and supervised methods. Experiments on SEED, SEED-IV, and MPED datasets show that the proposed model has remarkable advantages in learning more discriminative and general features for EEG emotional signals.
Keyword:
EEG emotion recognition
multi-task learning
self-supervised learning
graph neural network
期刊
IF:
9.8
论文数:
1.4K
被引数:
9.1K
机构
引用论文
Phase-Locking Value Based Graph Convolutional Neural Networks for Emotion Recognition.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏Catabolite inactivation of fructose‐1,6‐bisphosphatase in yeast is mediated by the proteasomeFEBS LettersOAAI
FEBS LettersIF0
OAAI分享收藏A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination predictionOAAI
IF0
OAAI分享收藏分享收藏MPED: A Multi-Model Physiological Emotion Database for Discrete Emotion RecongnitionIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏分享收藏
查看更多内容