Dielectric spectral profiles for andean tubers classification: a machine learning techniques application

Descripción del Articulo

El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
Detalles Bibliográficos
Autores: Chuquizuta Trigoso, Tony, Oblitas Cruz, Jimy, Arteaga Miñano, Hubert, Yarleque, Manuel, Castro Silupu, Wilson
Formato: objeto de conferencia
Fecha de Publicación:2021
Institución:Universidad Privada del Norte
Repositorio:UPN-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.upn.edu.pe:11537/31119
Enlace del recurso:https://hdl.handle.net/11537/31119
http://dx.doi.org/10.1109/ICEAA52647.2021.9539623
Nivel de acceso:acceso cerrado
Materia:Espectroscopia
Productos agrícolas
Tubérculos
Control de calidad
Industria
Spectroscopy
Quality control
Andean tubers
https://purl.org/pe-repo/ocde/ford#2.11.04
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dc.title.es_PE.fl_str_mv Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
title Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
spellingShingle Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
Chuquizuta Trigoso, Tony
Espectroscopia
Productos agrícolas
Tubérculos
Control de calidad
Industria
Spectroscopy
Quality control
Andean tubers
https://purl.org/pe-repo/ocde/ford#2.11.04
title_short Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
title_full Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
title_fullStr Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
title_full_unstemmed Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
title_sort Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
author Chuquizuta Trigoso, Tony
author_facet Chuquizuta Trigoso, Tony
Oblitas Cruz, Jimy
Arteaga Miñano, Hubert
Yarleque, Manuel
Castro Silupu, Wilson
author_role author
author2 Oblitas Cruz, Jimy
Arteaga Miñano, Hubert
Yarleque, Manuel
Castro Silupu, Wilson
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Chuquizuta Trigoso, Tony
Oblitas Cruz, Jimy
Arteaga Miñano, Hubert
Yarleque, Manuel
Castro Silupu, Wilson
dc.subject.es_PE.fl_str_mv Espectroscopia
Productos agrícolas
Tubérculos
Control de calidad
Industria
Spectroscopy
Quality control
Andean tubers
topic Espectroscopia
Productos agrícolas
Tubérculos
Control de calidad
Industria
Spectroscopy
Quality control
Andean tubers
https://purl.org/pe-repo/ocde/ford#2.11.04
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.11.04
description El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2022-08-09T20:28:25Z
dc.date.available.none.fl_str_mv 2022-08-09T20:28:25Z
dc.date.issued.fl_str_mv 2021-09-21
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.citation.es_PE.fl_str_mv Chuqizuta, T., ...[et al.]. (2021). Dielectric spectral profiles for andean tubers classification: a machine learning techniques application. 2021 International Conference on Electromagnetics in Advanced Applications, ICEAA. http://dx.doi.org/10.1109/ICEAA52647.2021.9539623
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11537/31119
dc.identifier.journal.es_PE.fl_str_mv 2021 International Conference on Electromagnetics in Advanced Applications, ICEAA
dc.identifier.doi.none.fl_str_mv http://dx.doi.org/10.1109/ICEAA52647.2021.9539623
identifier_str_mv Chuqizuta, T., ...[et al.]. (2021). Dielectric spectral profiles for andean tubers classification: a machine learning techniques application. 2021 International Conference on Electromagnetics in Advanced Applications, ICEAA. http://dx.doi.org/10.1109/ICEAA52647.2021.9539623
2021 International Conference on Electromagnetics in Advanced Applications, ICEAA
url https://hdl.handle.net/11537/31119
http://dx.doi.org/10.1109/ICEAA52647.2021.9539623
dc.language.iso.es_PE.fl_str_mv eng
language eng
dc.rights.es_PE.fl_str_mv info:eu-repo/semantics/closedAccess
eu_rights_str_mv closedAccess
dc.format.es_PE.fl_str_mv application/pdf
dc.publisher.es_PE.fl_str_mv IEEE
dc.publisher.country.es_PE.fl_str_mv US
dc.source.es_PE.fl_str_mv Universidad Privada del Norte
Repositorio Institucional - UPN
dc.source.none.fl_str_mv reponame:UPN-Institucional
instname:Universidad Privada del Norte
instacron:UPN
instname_str Universidad Privada del Norte
instacron_str UPN
institution UPN
reponame_str UPN-Institucional
collection UPN-Institucional
bitstream.url.fl_str_mv https://repositorio.upn.edu.pe/bitstream/11537/31119/1/license.txt
bitstream.checksum.fl_str_mv 8a4605be74aa9ea9d79846c1fba20a33
bitstream.checksumAlgorithm.fl_str_mv MD5
repository.name.fl_str_mv Repositorio Institucional UPN
repository.mail.fl_str_mv jordan.rivero@upn.edu.pe
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spelling Chuquizuta Trigoso, TonyOblitas Cruz, JimyArteaga Miñano, HubertYarleque, ManuelCastro Silupu, Wilson2022-08-09T20:28:25Z2022-08-09T20:28:25Z2021-09-21Chuqizuta, T., ...[et al.]. (2021). Dielectric spectral profiles for andean tubers classification: a machine learning techniques application. 2021 International Conference on Electromagnetics in Advanced Applications, ICEAA. http://dx.doi.org/10.1109/ICEAA52647.2021.9539623https://hdl.handle.net/11537/311192021 International Conference on Electromagnetics in Advanced Applications, ICEAAhttp://dx.doi.org/10.1109/ICEAA52647.2021.9539623El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.Currently, the agri-food industry prioritizes the development of non-destructive methods, such as dielectric spectroscopy, for quality control. The obtained dielectric spectral properties can be coupled to multivariate statistical methods as "machine learning" when identification of attributes is wanted. However, these techniques have not been applied to andean tubers classification. Therefore, the objective of the present investigation is to evaluate the possibility of discriminating four andean tubers using dielectric spectra properties and machine learning techniques (Support Vector Machine - SVM, K-Nearest Neighbors-KNN, and Linear Discriminat - LD). For this purpose, samples of Tropaeolum tuberosum (Killu isañu), Solanum tuberosa (yellow) and two varieties of Oxalis tuberosa (Puka kamusa and Lari oqa) were acquired, 30 units per tuber. The dielectric spectral profile was extracted twice for each tubers sample, in the range from 2 to 8 GHz. Then, the dielectric constant (e') were calculated, and its dimensionality was reduced using principal component analysis. Finally, models for classification were built by employing KNN, SVM and LD techniques. The results showed that three components can explain the variance at 99.6 %. Likewise, the accuracy in the discrimination values varied between 79.17 - 83.04, being SVM the best discrimination technique. Consequently, it is concluded that the technique of dielectric spectroscopy and machine learning presents potential for andean tuber discrimination.Revisión por paresCajamarcaapplication/pdfengIEEEUSinfo:eu-repo/semantics/closedAccessUniversidad Privada del NorteRepositorio Institucional - UPNreponame:UPN-Institucionalinstname:Universidad Privada del Norteinstacron:UPNEspectroscopiaProductos agrícolasTubérculosControl de calidadIndustriaSpectroscopyQuality controlAndean tubershttps://purl.org/pe-repo/ocde/ford#2.11.04Dielectric spectral profiles for andean tubers classification: a machine learning techniques applicationinfo:eu-repo/semantics/conferenceObjectLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.upn.edu.pe/bitstream/11537/31119/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5111537/31119oai:repositorio.upn.edu.pe:11537/311192022-08-09 15:58:25.334Repositorio Institucional UPNjordan.rivero@upn.edu.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Dielectric spectral profiles for andean tubers classification: a machine learning techniques application
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