An End-to-End Hemisphere Discrepancy Network for Subject-Independent Motor Imagery Classification.
Li NieHuan CaiYihan WuYangsong ZhangPublished in: ICONIP (3) (2021)
Keyphrases
- end to end
- motor imagery
- congestion control
- wireless ad hoc networks
- high bandwidth
- internet protocol
- transport layer
- eeg signals
- ad hoc networks
- classification accuracy
- admission control
- packet loss rate
- brain computer interface
- text localization and recognition
- machine learning
- pattern recognition
- differentiated services
- image classification
- feature selection
- rate adaptation
- eeg data
- feature space
- communication networks
- scalable video
- network structure
- computer networks
- neural network
- healthy subjects
- feature vectors
- feature set
- pattern classification