2015-07-07 Assigned to UNIVERSITY OF FLORIDA RESEARCH FOUNDATION, INC.
reassignment UNIVERSITY OF FLORIDA RESEARCH FOUNDATION, INC. ASSIGNMENT …

This article reviews advances in decoding methods for brain-machine interfaces (BMIs).
Recent work has focused on practical considerations for future clinical deployment of …

In studies of the nervous system, the choice of metric for the neural responses is a pivotal
assumption. For instance, a well-suited distance metric enables us to gauge the similarity of …

We introduce Enhanced Kernel-based Relevance Analysis (EKRA) that aims to support the
automatic identification of brain activity patterns using electroencephalographic recordings …

Person re-identification aims to identify the same person across different cameras, which is
widely applied in the intelligent monitoring field. The research of TriHard loss has been …

Micro-electrode arrays implanted into the brain record the electrical potentials
corresponding to the activity of neurons and neural populations. These recordings can be …

This paper presents a kernel-based relevance analysis to support student desertion
prediction. Our approach, termed KRA-SD, is twofold:(i) A feature ranking based on centered …

In this paper we proposed a metric learning-based method to extract collapsed buildings
from post-earthquake PolSAR imagery. In this method, eight building and orientation related …

Decoding movement related intentions is a key step to implement BMIs. Decoding EEG has
been challenging due to its low spatial resolution and signal to noise ratio. Metric learning …

Matrices are a common form of data encountered in a wide range of real applications. How
to efficiently classify this kind of data is an important research topic. In this paper, we …