Search Results for author:
Found 2 papers, 1 papers with code
Sparse Multitask Learning for Efficient Neural Representation of Motor Imagery and Execution
In the quest for efficient neural network models for neural data interpretation and user intent classification in brain-computer interfaces (BCIs), learning meaningful sparse representations of the underlying neural subspaces is crucial.
Calibration-Free Driver Drowsiness Classification based on Manifold-Level Augmentation
This paper proposes a calibration-free framework for driver drowsiness state classification using manifold-level augmentation.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
