Parallel Spatial–Temporal Self-Attention CNN-Based Motor Imagery Classification for BCI
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Title
Parallel Spatial–Temporal Self-Attention CNN-Based Motor Imagery Classification for BCI
Authors
Keywords
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Journal
Frontiers in Neuroscience
Volume 14, Issue -, Pages -
Publisher
Frontiers Media SA
Online
2020-12-11
DOI
10.3389/fnins.2020.587520
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- (2019) Syed Umar Amin et al. Future Generation Computer Systems-The International Journal of eScience
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- (2018) Jaydeep De et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- EEGNet: a compact convolutional neural network for EEG-based brain--computer interfaces
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- A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update
- (2018) F Lotte et al. Journal of Neural Engineering
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- (2018) Xuyang Zhu et al. Biomedical Signal Processing and Control
- Deep learning with convolutional neural networks for EEG decoding and visualization
- (2017) Robin Tibor Schirrmeister et al. HUMAN BRAIN MAPPING
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- (2017) Zhaoyang Qiu et al. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
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- (2017) Anmin Gong et al. JOURNAL OF MOTOR BEHAVIOR
- A new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension
- (2017) Manish Sharma et al. PATTERN RECOGNITION LETTERS
- Mixed Spectrum Analysis on fMRI Time-Series
- (2016) Arun Kumar et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
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- (2016) Yousef Rezaei Tabar et al. Journal of Neural Engineering
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- (2013) Alexandre Gramfort et al. NEUROIMAGE
- Brain–computer interfaces and communication in paralysis: Extinction of goal directed thinking in completely paralysed patients?
- (2008) A. Kübler et al. CLINICAL NEUROPHYSIOLOGY
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