A Multi-Domain Convolutional Neural Network for EEG-Based Motor Imagery Decoding
Author:
Affiliation:
1. School of Automation Science and Engineering, South China University of Technology, Guangdong, China
Funder
STI2030-Major Projects
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation
Link
http://xplorestaging.ieee.org/ielx7/7333/10031624/10275093.pdf?arnumber=10275093
Reference38 articles.
1. EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces
2. A Temporal-Spectral-Based Squeeze-and- Excitation Feature Fusion Network for Motor Imagery EEG Decoding
3. Deep learning with convolutional neural networks for EEG decoding and visualization
4. Motor Imagery EEG Decoding Method Based on a Discriminative Feature Learning Strategy
5. HS-CNN: a CNN with hybrid convolution scale for EEG motor imagery classification
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1. EEG-BCI-based motor imagery classification using double attention convolutional network;Computer Methods in Biomechanics and Biomedical Engineering;2024-01-02
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