Related references
Note: Only part of the references are listed.EEG Motor Imagery Classification With Sparse Spectrotemporal Decomposition and Deep Learning
Biao Sun et al.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2021)
Motor imagery recognition with automatic EEG channel selection and deep learning
Han Zhang et al.
JOURNAL OF NEURAL ENGINEERING (2021)
HS-CNN: a CNN with hybrid convolution scale for EEG motor imagery classification
Guanghai Dai et al.
JOURNAL OF NEURAL ENGINEERING (2020)
Multi-Label Image Recognition with Graph Convolutional Networks
Zhao-Min Chen et al.
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (2019)
EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces
Vernon J. Lawhern et al.
JOURNAL OF NEURAL ENGINEERING (2018)
A novel deep learning approach for classification of EEG motor imagery signals
Yousef Rezaei Tabar et al.
JOURNAL OF NEURAL ENGINEERING (2017)
Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naive Bayesian Classifier-based approach
Minmin Miao et al.
JOURNAL OF NEUROSCIENCE METHODS (2017)
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti et al.
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)
EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation
Suwicha Jirayucharoensak et al.
SCIENTIFIC WORLD JOURNAL (2014)
Improving the Separability of Motor Imagery EEG Signals Using a Cross Correlation-Based Least Square Support Vector Machine for Brain-Computer Interface
Siuly Siuly et al.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING (2012)