Lawhern, Vernon J.

Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials

Waytowich, N., Lawhern, V. J., Garcia, J. O., Cummings, J., Faller, J., Sajda, P., & Vettel, J. M. (2018) · Journal of Neural Engineering

EEG and Brain-Computer InterfacesGaze Tracking and Assistive Technology

Cited by 262

Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface

Waytowich, N. R., Lawhern, V. J., Bohannon, A. W., Ball, K. R., & Lance, B. J. (2016) · Frontiers in Neuroscience

EEG and Brain-Computer InterfacesGaze Tracking and Assistive Technology

Cited by 79

Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization

Wu, D., Lawhern, V. J., Hairston, W. D., & Lance, B. J. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering

EEG and Brain-Computer InterfacesDomain Adaptation and Few-Shot Learning

Cited by 74

EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features

Wu, D., Lance, B. J., Lawhern, V. J., Gordon, S., Jung, T.-P., & Lin, C.-T. (2017) · IEEE Transactions on Neural Systems and Rehabilitation Engineering

EEG and Brain-Computer InterfacesEmotion and Mood Recognition

Cited by 64

Improved Neural Signal Classification in a Rapid Serial Visual Presentation Task Using Active Learning

Marathe, A. R., Lawhern, V. J., Wu, D., Slayback, D., & Lance, B. J. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering

EEG and Brain-Computer InterfacesGaze Tracking and Assistive Technology

Cited by 64

Single-trial EEG RSVP classification using convolutional neural networks

Shamwell, J., Lee, H., Kwon, H., Marathe, A. R., Lawhern, V., & Nothwang, W. (2016) · SPIE Proceedings

EEG and Brain-Computer InterfacesGaze Tracking and Assistive Technology

Cited by 34

Real World BCI: Cross-Domain Learning and Practical Applications

Gordon, S. M., Jaswa, M., Solon, A. J., & Lawhern, V. J. (2017) · Proceedings of the 2017 ACM Workshop on An Application-oriented Approach to BCI out of the laboratory

EEG and Brain-Computer InterfacesEmotion and Mood Recognition

Cited by 20

Cortically Coupled Computing: A New Paradigm for Synergistic Human-Machine Interaction

Saproo, S., Faller, J., Shih, V., Sajda, P., Waytowich, N. R., Bohannon, A., Lawhern, V. J., Lance, B. J., & Jangraw, D. (2016) · Computer

EEG and Brain-Computer InterfacesCognitive Computing and Networks

Cited by 18