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Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12590/16897
Title: A method based on rf spectral featuresfor evaluating the porosity degree in ceramic materials
Authors: Sanchez Suarez, Rudy Marcelino
metadata.dc.contributor.advisor: Choquehuanca Zevallos, Juan José
Keywords: Classification;Machine learning;SVM;Ceramic materials;Porosity;Radio frequency
Issue Date: 2018
Publisher: IEEE
metadata.dc.relation.uri: https://ieeexplore.ieee.org/document/8699066
Abstract: In this paper, a classification system of the degree of porosity of ceramic materials based on a Radio Frequency system is presented. The system uses methods from the machine learning field to learn patterns from spectral features measured with a circular patch antenna. Experimental results show that it is possible to indirectly get an estimate of the degree of porosity of ceramic samples getting low classification error rates.
URI: http://hdl.handle.net/20.500.12590/16897
ISBN: urn:isbn:9781538673331
Appears in Collections:Artículos - Ingeniería Electrónica y de Telecomunicaciones

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