Deep Neural Network With Joint Distribution Matching for Cross-Subject Motor Imagery Brain-Computer Interfaces

BioMed Research International - United States
doi 10.1155/2020/7285057
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Hindawi Limited

Related search

Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces

Advances in Science, Technology and Engineering Systems
EngineeringAstronomyPhysicsManagement of TechnologyInnovation
2017English

Building Extraction From Very High Resolution Aerial Imagery Using Joint Attention Deep Neural Network

Remote Sensing
EarthPlanetary Sciences
2019English

Is Implicit Motor Imagery a Reliable Strategy for a Brain–Computer Interface?

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Internal MedicineMedicineComputer Science ApplicationsBiomedical EngineeringNeuroscience
2017English

Brain-Computer Interfaces

Human-Computer Interaction Series
2010English

Realistic Expectations With Brain Computer Interfaces

Journal of Assistive Technologies
2012English

Semiotic Training for Brain-Computer Interfaces

2016English

Investergating Characteristics of a Motor Imagery Based Brain-Computer Interface With Quick-Response Tactile Feedback

2019English

High Classification Accuracy of a Motor Imagery Based Brain-Computer Interface for Stroke Rehabilitation Training

Frontiers Robotics AI
Computer Science ApplicationsArtificial Intelligence
2018English

Modern Electrophysiological Methods for Brain-Computer Interfaces

Computational Intelligence and Neuroscience
MedicineMathematicsComputer ScienceNeuroscience
2007English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy