Inter-Subject Transfer Learning Using Euclidean Alignment and Transfer Component Analysis for Motor Imagery-Based BCI-Reference-Cited by-同舟云学术

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Inter-Subject Transfer Learning Using Euclidean Alignment and Transfer Component Analysis for Motor Imagery-Based BCI

Published:2021-10-17 Issue: Volume: Page:
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Container-title:2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
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Author:

Demsy Orvin,Achanccaray David,Hayashibe Mitsuhiro

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9658572/9658575/09658731.pdf?arnumber=9658731

Reference18 articles.

1. Stationary Transfer Component Analysis for Brain Computer Interfacing

2. Transfer components between subjects for EEG-based emotion recognition

3. Transfer Learning for Brain-Computer Interfaces: A Complete Pipeline;wu,2020

4. BCI Competition IV 2008 – Graz data set A;brunner,2008

5. Optimizing Spatial filters for Robust EEG Single-Trial Analysis

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1. A systematic evaluation of Euclidean alignment with deep learning for EEG decoding;Journal of Neural Engineering;2024-06-01

2. Comparison of Domain Selection Methods for Multi-Source Manifold Feature Transfer Learning in Electroencephalogram Classification;Applied Sciences;2024-03-10

3. Impact monitoring on complex structure using VMD-MPE feature extraction and transfer learning;Ultrasonics;2024-01

4. Multi-Class Transfer Learning and Domain Selection for Cross-Subject EEG Classification;Applied Sciences;2023-04-21

5. Motor Imagery-based BCI Perspective in Procedure and Analysis;Highlights in Science, Engineering and Technology;2023-03-21

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