Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network

Autores
Corchado, Emilio; Fyfe, Colin
Año de publicación
2002
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this paper, we study the problem of identification of underlying causes from a mixture of causes when these causes interfere with one another in a particular manner: the causes we consider are visual inputs to a neural network system which are created by independent underlying causes which may occlude each other. The prototypical problem in this area is a mixture of horizontal and vertical bars in which each horizontal bar interferes with the representation of each vertical bar and vice versa. We develop an unsupervised neural network which is able to identify a single orientation of bars from a mixture of horizontal and vertical bars.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
unsupervised neural network
underlying causes
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:10915/183167
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/183167
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Suppression of Related Independent Causes Using An Unsupervised Artificial Neural NetworkCorchado, EmilioFyfe, ColinCiencias Informáticasunsupervised neural networkunderlying causesIn this paper, we study the problem of identification of underlying causes from a mixture of causes when these causes interfere with one another in a particular manner: the causes we consider are visual inputs to a neural network system which are created by independent underlying causes which may occlude each other. The prototypical problem in this area is a mixture of horizontal and vertical bars in which each horizontal bar interferes with the representation of each vertical bar and vice versa. We develop an unsupervised neural network which is able to identify a single orientation of bars from a mixture of horizontal and vertical bars.Sociedad Argentina de Informática e Investigación Operativa2002info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf130-141http://sedici.unlp.edu.ar/handle/10915/183167enginfo:eu-repo/semantics/altIdentifier/issn/1660-1079info: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:UNLP2025-09-03T11:21:45Zoai:sedici.unlp.edu.ar:10915/183167Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:21:45.785SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network
title Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network
spellingShingle Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network
Corchado, Emilio
Ciencias Informáticas
unsupervised neural network
underlying causes
title_short Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network
title_full Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network
title_fullStr Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network
title_full_unstemmed Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network
title_sort Suppression of Related Independent Causes Using An Unsupervised Artificial Neural Network
dc.creator.none.fl_str_mv Corchado, Emilio
Fyfe, Colin
author Corchado, Emilio
author_facet Corchado, Emilio
Fyfe, Colin
author_role author
author2 Fyfe, Colin
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
unsupervised neural network
underlying causes
topic Ciencias Informáticas
unsupervised neural network
underlying causes
dc.description.none.fl_txt_mv In this paper, we study the problem of identification of underlying causes from a mixture of causes when these causes interfere with one another in a particular manner: the causes we consider are visual inputs to a neural network system which are created by independent underlying causes which may occlude each other. The prototypical problem in this area is a mixture of horizontal and vertical bars in which each horizontal bar interferes with the representation of each vertical bar and vice versa. We develop an unsupervised neural network which is able to identify a single orientation of bars from a mixture of horizontal and vertical bars.
Sociedad Argentina de Informática e Investigación Operativa
description In this paper, we study the problem of identification of underlying causes from a mixture of causes when these causes interfere with one another in a particular manner: the causes we consider are visual inputs to a neural network system which are created by independent underlying causes which may occlude each other. The prototypical problem in this area is a mixture of horizontal and vertical bars in which each horizontal bar interferes with the representation of each vertical bar and vice versa. We develop an unsupervised neural network which is able to identify a single orientation of bars from a mixture of horizontal and vertical bars.
publishDate 2002
dc.date.none.fl_str_mv 2002
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/10915/183167
url http://sedici.unlp.edu.ar/handle/10915/183167
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1660-1079
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
130-141
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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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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score 13.13397

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