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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/153125
Ver los metadatos del registro completo
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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:UNLP2025-09-29T11:39:22Zoai: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:13292025-09-29 11:39:22.9SEDICI (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 |
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conferenceObject |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/153125 |
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http://sedici.unlp.edu.ar/handle/10915/153125 |
dc.language.none.fl_str_mv |
eng |
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eng |
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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) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 791-798 |
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