Thinker invariance: enabling deep neural networks for BCI across more people.
Journal:
Journal of neural engineering
Published Date:
Oct 13, 2020
Abstract
OBJECTIVE: Most deep neural networks (DNNs) used as brain computer interfaces (BCI) classifiers are rarely viable for more than one person and are relatively shallow compared to the state-of-the-art in the wider machine learning literature. The goal of this work is to frame these as a unified challenge and reconsider how transfer learning is used to overcome these difficulties.