Federated deep transfer learning for EEG decoding using multiple BCI tasks

Noise-Factorized Disentangled Representation Learning for Generalizable Motor Imagery EEG Classification

J Han, X Gu, GZ Yang, B Lo - IEEE Journal of Biomedical and …, 2023 - ieeexplore.ieee.org
Motor Imagery (MI) Electroencephalography (EEG) is one of the most common Brain-
Computer Interface (BCI) paradigms that has been widely used in neural rehabilitation and …
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Adaptive Federated Learning for EEG Emotion Recognition

C Chan, Q Zheng, C Xu, Q Wang… - 2024 International Joint …, 2024 - ieeexplore.ieee.org
Emotion classification based on electroencephalogram (EEG) signals has drawn huge
attention in affective brain computer interface (BCI). Recently, plenty of deep learning …
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[HTML][HTML] Transfer Learning for Non-Invasive BCI EEG Brainwave Decoding

X Wei - 2024 - intechopen.com
Brain-computer interfaces (BCIs) represent a rapidly advancing domain that enables the
interpretation of human cognitive states and intentions through brainwave analysis. This …
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Federated Learning for Enhanced Deep Learning Integration: A Practical Approach

T Upadhyay, D Patadia, S Mittal - The International Conference on Recent …, 2023 - Springer
Federated learning offers a convincing resolution to the urgent challenges of data privacy,
communication capacity, and scalability that afflict conventional centralized learning …
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