Minima Possible Weights: A Homogenous Deep Ensemble Method for Cross-Subject Motor Imagery Classification

Motor Imagery (MI) systems in Brain-Computer Interface (BCI) research provide communication and control solutions for individuals with motor impairments, yet cross-subject classification remains challenging due to substantial inter-subject variability. In this study, we propose the Minima Possible W...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Quang Pham Lam Dinh, Isao Nambu
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Brain-computer interface cross-subject deep ensemble learning multi-class classification motor imagery unsupervised learning
Online Access:	https://ieeexplore.ieee.org/document/10878971/