Privacy-Preserving Domain Adaptation for Intracranial EEG Classification via Information Maximization and Gaussian Mixture Model-Reference-Cited by-同舟云学术

Privacy-Preserving Domain Adaptation for Intracranial EEG Classification via Information Maximization and Gaussian Mixture Model

Published:2023-11-01 Issue:21 Volume:23 Page:26390-26400
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wang Kun¹^ORCID,Yang Ming¹,Li Chang²^ORCID,Liu Aiping¹^ORCID,Qian Ruobing³^ORCID,Chen Xun¹^ORCID

Affiliation:

1. School of Information Science and Technology, University of Science and Technology of China, Hefei, China

2. Department of Biomedical Engineering, Hefei University of Technology, Hefei, China

3. Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China

Funder

National Natural Science Foundation of China

Joint Fund for Medical Artificial Intelligence

Research Project of Health Commission of Anhui Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10302460/10268883.pdf?arnumber=10268883

Reference38 articles.

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3. Utilization of temporal autoencoder for semi-supervised intracranial EEG clustering and classification

4. Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

5. IEEG-TCN: A Concise and Robust Temporal Convolutional Network for Intracranial Electroencephalogram Signal Identification

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