Artificial Neural Network-based Model Used to Determine Citric Maturity Level

Autores
Sampallo, Guillermo M.; Karanik, Marcelo J.; Gramajo, Sergio D.; González Thomas, Arturo; Varone, Leandro
Año de publicación
2010
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
One of the most important tasks in price determination of a product is the classification for its quality, color, maturity, etc. Usually vegetables and fruits are classified manually. This process is complex and usually some errors in the product categorization occur due to the subjectivity of persons with limited skills and long hours’ work. A possible alternative is the automatic selection of products using classifiers based on computer vision systems. These systems capture the image of the product and determine its class in real time. In this paper a model capable of establishing the level of maturity of oranges, using artificial neural networks, is proposed.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Computer Vision Systems
Artificial Neural Networks
Multi Layer Perceptron
image classification
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/153125
Acceder
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network_name_str SEDICI (UNLP)
spelling Artificial Neural Network-based Model Used to Determine Citric Maturity LevelSampallo, Guillermo M.Karanik, Marcelo J.Gramajo, Sergio D.González Thomas, ArturoVarone, LeandroCiencias InformáticasComputer Vision SystemsArtificial Neural NetworksMulti Layer Perceptronimage classificationOne of the most important tasks in price determination of a product is the classification for its quality, color, maturity, etc. Usually vegetables and fruits are classified manually. This process is complex and usually some errors in the product categorization occur due to the subjectivity of persons with limited skills and long hours’ work. A possible alternative is the automatic selection of products using classifiers based on computer vision systems. These systems capture the image of the product and determine its class in real time. In this paper a model capable of establishing the level of maturity of oranges, using artificial neural networks, is proposed.Sociedad Argentina de Informática e Investigación Operativa2010info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf791-798http://sedici.unlp.edu.ar/handle/10915/153125enginfo:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-cai-15.pdfinfo:eu-repo/semantics/altIdentifier/issn/1852-4850info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:31:10Zoai:sedici.unlp.edu.ar:10915/153125Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:31:10.281SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Artificial Neural Network-based Model Used to Determine Citric Maturity Level
title Artificial Neural Network-based Model Used to Determine Citric Maturity Level
spellingShingle Artificial Neural Network-based Model Used to Determine Citric Maturity Level
Sampallo, Guillermo M.
Ciencias Informáticas
Computer Vision Systems
Artificial Neural Networks
Multi Layer Perceptron
image classification
title_short Artificial Neural Network-based Model Used to Determine Citric Maturity Level
title_full Artificial Neural Network-based Model Used to Determine Citric Maturity Level
title_fullStr Artificial Neural Network-based Model Used to Determine Citric Maturity Level
title_full_unstemmed Artificial Neural Network-based Model Used to Determine Citric Maturity Level
title_sort Artificial Neural Network-based Model Used to Determine Citric Maturity Level
dc.creator.none.fl_str_mv Sampallo, Guillermo M.
Karanik, Marcelo J.
Gramajo, Sergio D.
González Thomas, Arturo
Varone, Leandro
author Sampallo, Guillermo M.
author_facet Sampallo, Guillermo M.
Karanik, Marcelo J.
Gramajo, Sergio D.
González Thomas, Arturo
Varone, Leandro
author_role author
author2 Karanik, Marcelo J.
Gramajo, Sergio D.
González Thomas, Arturo
Varone, Leandro
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Computer Vision Systems
Artificial Neural Networks
Multi Layer Perceptron
image classification
topic Ciencias Informáticas
Computer Vision Systems
Artificial Neural Networks
Multi Layer Perceptron
image classification
dc.description.none.fl_txt_mv One of the most important tasks in price determination of a product is the classification for its quality, color, maturity, etc. Usually vegetables and fruits are classified manually. This process is complex and usually some errors in the product categorization occur due to the subjectivity of persons with limited skills and long hours’ work. A possible alternative is the automatic selection of products using classifiers based on computer vision systems. These systems capture the image of the product and determine its class in real time. In this paper a model capable of establishing the level of maturity of oranges, using artificial neural networks, is proposed.
Sociedad Argentina de Informática e Investigación Operativa
description One of the most important tasks in price determination of a product is the classification for its quality, color, maturity, etc. Usually vegetables and fruits are classified manually. This process is complex and usually some errors in the product categorization occur due to the subjectivity of persons with limited skills and long hours’ work. A possible alternative is the automatic selection of products using classifiers based on computer vision systems. These systems capture the image of the product and determine its class in real time. In this paper a model capable of establishing the level of maturity of oranges, using artificial neural networks, is proposed.
publishDate 2010
dc.date.none.fl_str_mv 2010
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/153125
url http://sedici.unlp.edu.ar/handle/10915/153125
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-cai-15.pdf
info:eu-repo/semantics/altIdentifier/issn/1852-4850
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
791-798
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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