Hyperspectrum comparison using similarity measures

Date

2017-08-31

Director

Publisher

IEEE
Acceso abierto / Sarbide irekia
Contribución a congreso / Biltzarrerako ekarpena
Versión aceptada / Onetsi den bertsioa

Project identifier

  • MINECO//RTA2013-00006-C03-03/ES/ recolecta
  • MINECO//TIN2016-77356-P/
Impacto
OpenAlexGoogle Scholar
cited by count

Abstract

Similarity measures, as studied in the context of fuzzy set theory, have been proven applicable to many different fields. Surely, their primary role is to model the perceived (dis-) similarity between two fuzzy sets or, equivalently, the linguistic terms they represent. However, the richness of the dedicated study makes the similarity measures portable to other contexts in which quantitative comparison plays a key role. In this work we present the application of similarity measures to hyperspectrum comparison in the context of in-lab hyperspectral imaging for bioengineering.

Description

Keywords

Hyperspectral imaging, Fuzzy sets, Fuzzy set theory, Psychology, Wavelength measurement, Pragmatics

Department

Automática y Computación / Automatika eta Konputazioa / Proyectos e Ingeniería Rural / Landa Ingeniaritza eta Proiektuak

Faculty/School

Degree

Doctorate program

item.page.cita

López-Molina, C., Marco-Detchart, C., Bustince, H., Fernández, J., López-Maestresalas, A., Ayala-Martini, D. (2017) Hyperspectrum comparison using similarity measures. In Hayashi, I., Díaz I., 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS) (pp. 1-6). IEEE. https://doi.org/10.1109/IFSA-SCIS.2017.8023259

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