Jun 3, 2021 · Deep neural network is a promising method to recognize motor imagery electroencephalography (MI-EEG), which is often used as the source ...
Deep neural network is a promising method to recognize motor imagery electroencephalography (MI-EEG), which is often used as the source signal of a ...
Key Band Image Sequences and A Hybrid Deep Neural Network for Recognition of Motor Imagery EEG · Ming-ai Li, Wei Peng, Jin-Fu Yang · Published in IEEE Access 2021 ...
ABSTRACT Deep neural network is a promising method to recognize motor imagery electroencephalography (MI-EEG), which is often used as the source signal of a ...
Deep neural network is a promising method to recognize motor imagery electroencephalography (MI-EEG), which is often used as the source signal of a ...
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Nov 1, 2023 · In this article, we propose a transformer-based deep learning neural network architecture that performs motion recognition on the raw BCI competition III IVa ...
Structure of the parallel multimodule CNN. - ResearchGate
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Deep neural network is a promising method to recognize motor imagery electroencephalography (MI-EEG), which is often used as the source signal of a ...
We propose an end-to-end deep neural network that automatically finds and combines features for motor imagery (MI) based EEG BCI with 4 or more imagery classes ...
In this paper, we design a min-VGG-LSTMnet hybrid deep learning network to solve the problem of low recognition accuracy of multi-class task. It combines Long ...
We comprehensively review DL-based MI-EEG classification models, including network architectures, systematic categorizations, summaries of input formulations, ...
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