Description

Scale Space Theory is a Computer Vision technique that can be used to implement shallow machine learning algorithms which are invariant to scales. It is known that EEG signals have invariances in scale, and it is very likely that this theory can be used to detect neuralcorrelates.

Scope

It can be applied for motor intention detection.

Code

• https://github.com/faturita/Gsync