A novel method for classification of BCI multi-class motor imagery task based on Dempster–Shafer theory

2019 ◽  
Vol 484 ◽  
pp. 14-26 ◽  
Author(s):  
Sara Razi ◽  
Mohammad Reza Karami Mollaei ◽  
Jamal Ghasemi
Keyword(s):  
Motor Imagery ◽  
Imagery Task ◽  
Dempster Shafer Theory ◽  
Novel Method ◽  
Shafer Theory

Classification of Motor Imagery Task by Using Novel Ensemble Pruning Approach

2020 ◽  
Vol 28 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Muhammad Ammar Ali ◽  
Duygu Ucuncu ◽  
Pinar Karadayi Atas ◽  
Sureyya Ozogur-Akyuz
Keyword(s):  
Motor Imagery ◽  
Imagery Task ◽  
Ensemble Pruning

Classification of a complex landscape using Dempster–Shafer theory of evidence

2006 ◽  
Vol 27 (10) ◽  
pp. 1951-1971 ◽  
Author(s):  
L. Cayuela ◽  
J. D. Golicher ◽  
J. Salas Rey ◽  
J. M. Rey Benayas
Keyword(s):  
Dempster Shafer Theory ◽  
Complex Landscape ◽  
Shafer Theory ◽  
Theory Of Evidence

scholarly journals Application of the Dempster-Shafer Theory to the Classification of Pixels from Aster Satellite Images and Spectral Indices

2017 ◽  
Vol 05 (07) ◽  
pp. 1462-1477 ◽  
Author(s):  
Jean-Claude Okaingni ◽  
Sié Ouattara ◽  
Adles Francis Kouassi ◽  
Adama Koné ◽  
Wognin Joseph Vangah ◽  
...  
Keyword(s):  
Satellite Images ◽  
Spectral Indices ◽  
Dempster Shafer Theory ◽  
Shafer Theory

Optimising Object Classification

2008 ◽  
pp. 234-253 ◽  
Author(s):  
Malcolm J. Beynon
Keyword(s):  
Object Classification ◽  
Original Data ◽  
Classification Problem ◽  
Uncertain Reasoning ◽  
Objective Functions ◽  
Data Set ◽  
Dempster Shafer Theory ◽  
Novel Approach ◽  
Shafer Theory

This chapter investigates the effectiveness of a number of objective functions used in conjunction with a novel technique to optimise the classification of objects based on a number of characteristic values, which may or may not be missing. The classification and ranking belief simplex (CaRBS) technique is based on Dempster-Shafer theory and, hence, operates in the presence of ignorance. The objective functions considered minimise the level of ambiguity and/or ignorance in the classification of companies to being either failed or not-failed. Further results are found when an incomplete version of the original data set is considered. The findings in this chapter demonstrate how techniques such as CaRBS, which operate in an uncertain reasoning based environment, offer a novel approach to object classification problem solving.

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