VAEEG: Variational auto-encoder for extracting EEG representation

VAEEG: Variational auto-encoder for extracting EEG representation

The electroencephalogram (EEG) exhibits characteristics of complexity and strong randomness. Existing deep learning models for EEG typically target specific objectives and datasets, with their scalability constrained by the size of the dataset, resulting in limited perceptual and generalization abil...

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Bibliographic Details
Main Authors: Tong Zhao, Yi Cui, Taoyun Ji, Jiejian Luo, Wenling Li, Jun Jiang, Zaifen Gao, Wenguang Hu, Yuxiang Yan, Yuwu Jiang, Bo Hong
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:NeuroImage
Subjects:
EEG representation
Variational auto-encoder (VAE)
Pediatric brain development
Epileptic seizure
Sleep stage classification
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811924004439

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http://www.sciencedirect.com/science/article/pii/S1053811924004439

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