Reconstruction of Iberian ceramic potteries using generative adversarial networks

Autores
Navarro, Jose Pablo; Cintas, Celia; Lucena, Manuel; Fuertes, José Manuel; Segura, Rafael; Delrieux, Claudio Augusto; Gonzalez-Jose, Rolando
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Several aspects of past culture, including historical trends, are inferred from time-based patterns observed in archaeological artifacts belonging to different periods. The presence and variation of these objects provides important clues about the Neolithic revolution and given their relative abundance in most archaeological sites, ceramic potteries are significantly helpful in this purpose. Nonetheless, most available pottery is fragmented, leading to missing morphological information. Currently, the reassembly of fragmented objects from a collection of thousands of mixed fragments is a daunting and time-consuming task done almost exclusively by hand, which requires the physical manipulation of the fragments. To overcome the challenges of manual reconstruction and improve the quality of reconstructed samples, we present IberianGAN, a customized Generative Adversarial Network (GAN) tested on an extensive database with complete and fragmented references. We trained the model with 1072 samples corresponding to Iberian wheel-made pottery profiles belonging to archaeological sites located in the upper valley of the Guadalquivir River (Spain). Furthermore, we provide quantitative and qualitative assessments to measure the quality of the reconstructed samples, along with domain expert evaluation with archaeologists. The resulting framework is a possible way to facilitate pottery reconstruction from partial fragments of an original piece.
Fil: Navarro, Jose Pablo. Universidad Nacional de la Patagonia "San Juan Bosco". Facultad de Ingeniería - Sede Puerto Madryn. Departamento de Informática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; Argentina
Fil: Cintas, Celia. Catholic University Of Eastern Africa; Kenia
Fil: Lucena, Manuel. Universidad de Jaén; España
Fil: Fuertes, José Manuel. Universidad de Jaén; España
Fil: Segura, Rafael. Universidad de Jaén; España
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur; Argentina
Fil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; Argentina
Materia
Iberian ceramic
Generative adversarial networks
Deep learning
Archaeology
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/205249
Acceder
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spelling Reconstruction of Iberian ceramic potteries using generative adversarial networksNavarro, Jose PabloCintas, CeliaLucena, ManuelFuertes, José ManuelSegura, RafaelDelrieux, Claudio AugustoGonzalez-Jose, RolandoIberian ceramicGenerative adversarial networksDeep learningArchaeologyhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Several aspects of past culture, including historical trends, are inferred from time-based patterns observed in archaeological artifacts belonging to different periods. The presence and variation of these objects provides important clues about the Neolithic revolution and given their relative abundance in most archaeological sites, ceramic potteries are significantly helpful in this purpose. Nonetheless, most available pottery is fragmented, leading to missing morphological information. Currently, the reassembly of fragmented objects from a collection of thousands of mixed fragments is a daunting and time-consuming task done almost exclusively by hand, which requires the physical manipulation of the fragments. To overcome the challenges of manual reconstruction and improve the quality of reconstructed samples, we present IberianGAN, a customized Generative Adversarial Network (GAN) tested on an extensive database with complete and fragmented references. We trained the model with 1072 samples corresponding to Iberian wheel-made pottery profiles belonging to archaeological sites located in the upper valley of the Guadalquivir River (Spain). Furthermore, we provide quantitative and qualitative assessments to measure the quality of the reconstructed samples, along with domain expert evaluation with archaeologists. The resulting framework is a possible way to facilitate pottery reconstruction from partial fragments of an original piece.Fil: Navarro, Jose Pablo. Universidad Nacional de la Patagonia "San Juan Bosco". Facultad de Ingeniería - Sede Puerto Madryn. Departamento de Informática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; ArgentinaFil: Cintas, Celia. Catholic University Of Eastern Africa; KeniaFil: Lucena, Manuel. Universidad de Jaén; EspañaFil: Fuertes, José Manuel. Universidad de Jaén; EspañaFil: Segura, Rafael. Universidad de Jaén; EspañaFil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur; ArgentinaFil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; ArgentinaNature Publishing Group2022-06-23info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/205249Navarro, Jose Pablo; Cintas, Celia; Lucena, Manuel; Fuertes, José Manuel; Segura, Rafael; et al.; Reconstruction of Iberian ceramic potteries using generative adversarial networks; Nature Publishing Group; Scientific Reports; 12; 1; 23-6-2022; 1-112045-2322CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-022-14910-7info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-022-14910-7info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:46:18Zoai:ri.conicet.gov.ar:11336/205249instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:46:18.572CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Reconstruction of Iberian ceramic potteries using generative adversarial networks
title Reconstruction of Iberian ceramic potteries using generative adversarial networks
spellingShingle Reconstruction of Iberian ceramic potteries using generative adversarial networks
Navarro, Jose Pablo
Iberian ceramic
Generative adversarial networks
Deep learning
Archaeology
title_short Reconstruction of Iberian ceramic potteries using generative adversarial networks
title_full Reconstruction of Iberian ceramic potteries using generative adversarial networks
title_fullStr Reconstruction of Iberian ceramic potteries using generative adversarial networks
title_full_unstemmed Reconstruction of Iberian ceramic potteries using generative adversarial networks
title_sort Reconstruction of Iberian ceramic potteries using generative adversarial networks
dc.creator.none.fl_str_mv Navarro, Jose Pablo
Cintas, Celia
Lucena, Manuel
Fuertes, José Manuel
Segura, Rafael
Delrieux, Claudio Augusto
Gonzalez-Jose, Rolando
author Navarro, Jose Pablo
author_facet Navarro, Jose Pablo
Cintas, Celia
Lucena, Manuel
Fuertes, José Manuel
Segura, Rafael
Delrieux, Claudio Augusto
Gonzalez-Jose, Rolando
author_role author
author2 Cintas, Celia
Lucena, Manuel
Fuertes, José Manuel
Segura, Rafael
Delrieux, Claudio Augusto
Gonzalez-Jose, Rolando
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Iberian ceramic
Generative adversarial networks
Deep learning
Archaeology
topic Iberian ceramic
Generative adversarial networks
Deep learning
Archaeology
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Several aspects of past culture, including historical trends, are inferred from time-based patterns observed in archaeological artifacts belonging to different periods. The presence and variation of these objects provides important clues about the Neolithic revolution and given their relative abundance in most archaeological sites, ceramic potteries are significantly helpful in this purpose. Nonetheless, most available pottery is fragmented, leading to missing morphological information. Currently, the reassembly of fragmented objects from a collection of thousands of mixed fragments is a daunting and time-consuming task done almost exclusively by hand, which requires the physical manipulation of the fragments. To overcome the challenges of manual reconstruction and improve the quality of reconstructed samples, we present IberianGAN, a customized Generative Adversarial Network (GAN) tested on an extensive database with complete and fragmented references. We trained the model with 1072 samples corresponding to Iberian wheel-made pottery profiles belonging to archaeological sites located in the upper valley of the Guadalquivir River (Spain). Furthermore, we provide quantitative and qualitative assessments to measure the quality of the reconstructed samples, along with domain expert evaluation with archaeologists. The resulting framework is a possible way to facilitate pottery reconstruction from partial fragments of an original piece.
Fil: Navarro, Jose Pablo. Universidad Nacional de la Patagonia "San Juan Bosco". Facultad de Ingeniería - Sede Puerto Madryn. Departamento de Informática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; Argentina
Fil: Cintas, Celia. Catholic University Of Eastern Africa; Kenia
Fil: Lucena, Manuel. Universidad de Jaén; España
Fil: Fuertes, José Manuel. Universidad de Jaén; España
Fil: Segura, Rafael. Universidad de Jaén; España
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur; Argentina
Fil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; Argentina
description Several aspects of past culture, including historical trends, are inferred from time-based patterns observed in archaeological artifacts belonging to different periods. The presence and variation of these objects provides important clues about the Neolithic revolution and given their relative abundance in most archaeological sites, ceramic potteries are significantly helpful in this purpose. Nonetheless, most available pottery is fragmented, leading to missing morphological information. Currently, the reassembly of fragmented objects from a collection of thousands of mixed fragments is a daunting and time-consuming task done almost exclusively by hand, which requires the physical manipulation of the fragments. To overcome the challenges of manual reconstruction and improve the quality of reconstructed samples, we present IberianGAN, a customized Generative Adversarial Network (GAN) tested on an extensive database with complete and fragmented references. We trained the model with 1072 samples corresponding to Iberian wheel-made pottery profiles belonging to archaeological sites located in the upper valley of the Guadalquivir River (Spain). Furthermore, we provide quantitative and qualitative assessments to measure the quality of the reconstructed samples, along with domain expert evaluation with archaeologists. The resulting framework is a possible way to facilitate pottery reconstruction from partial fragments of an original piece.
publishDate 2022
dc.date.none.fl_str_mv 2022-06-23
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/205249
Navarro, Jose Pablo; Cintas, Celia; Lucena, Manuel; Fuertes, José Manuel; Segura, Rafael; et al.; Reconstruction of Iberian ceramic potteries using generative adversarial networks; Nature Publishing Group; Scientific Reports; 12; 1; 23-6-2022; 1-11
2045-2322
CONICET Digital
CONICET
url http://hdl.handle.net/11336/205249
identifier_str_mv Navarro, Jose Pablo; Cintas, Celia; Lucena, Manuel; Fuertes, José Manuel; Segura, Rafael; et al.; Reconstruction of Iberian ceramic potteries using generative adversarial networks; Nature Publishing Group; Scientific Reports; 12; 1; 23-6-2022; 1-11
2045-2322
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-022-14910-7
info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-022-14910-7
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Publishing Group
publisher.none.fl_str_mv Nature Publishing Group
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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