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Spectral Reflectance Reconstruction Using Fuzzy Logic System Training: Color Science Application

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Spectral Reflectance Reconstruction Using Fuzzy Logic System Training: Color Science Application

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Amiri, MM.; Garcia-Nieto, S.; Morillas, S.; Fairchild, MD. (2020). Spectral Reflectance Reconstruction Using Fuzzy Logic System Training: Color Science Application. Sensors. 20(17):1-18. https://doi.org/10.3390/s20174726

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/176450

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Title: Spectral Reflectance Reconstruction Using Fuzzy Logic System Training: Color Science Application
Author: Amiri, Morteza Maali Garcia-Nieto, Sergio Morillas, Samuel Fairchild, Mark D.
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica
Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Issued date:
Abstract:
[EN] In this work, we address the problem of spectral reflectance recovery from both CIEXYZ and RGB values by means of a machine learning approach within the fuzzy logic framework, which constitutes the first application ...[+]
Subjects: Spectral recovery , CIEXYZ , RGB , Fuzzy logic , Fuzzy logic inference systems
Copyrigths: Reconocimiento (by)
Source:
Sensors. (eissn: 1424-8220 )
DOI: 10.3390/s20174726
Publisher:
MDPI AG
Publisher version: https://doi.org/10.3390/s20174726
Project ID:
info:eu-repo/grantAgreement/Ministerio de Educación Cultura y Deporte//PRX16%2F00050//Medidas de similitud perceptual para imágenes en color/
info:eu-repo/grantAgreement/Ministerio de Educación Cultura y Deporte//PRX17%2F00384//Medidas de calidad perceptual para imágenes en color/
info:eu-repo/grantAgreement/AEI//PID2019-107790RB-C22//DESARROLLO DEL SOFTWARE PARA UN SISTEMA PET DE CRISTAL CONTINUO APLICADO AL CANCER DE MAMA/
Thanks:
Samuel Morillas acknowledges the support of the Spanish Ministry of Science under grants PRX17/00384, PRX16/00050 and PID2019-107790RB-C22.
Type: Artículo

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