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A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies

Cultural heritage images are among the primary media for communicating and preserving the cultural values of a society. The images represent concrete and abstract content and symbolise the social, economic, political, and cultural values of the society. However, an enormous amount of such values emb...

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Autores principales: Abgaz, Yalemisew, Rocha Souza, Renato, Methuku, Japesh, Koch, Gerda, Dorn, Amelie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404920/
https://www.ncbi.nlm.nih.gov/pubmed/34460757
http://dx.doi.org/10.3390/jimaging7080121
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author Abgaz, Yalemisew
Rocha Souza, Renato
Methuku, Japesh
Koch, Gerda
Dorn, Amelie
author_facet Abgaz, Yalemisew
Rocha Souza, Renato
Methuku, Japesh
Koch, Gerda
Dorn, Amelie
author_sort Abgaz, Yalemisew
collection PubMed
description Cultural heritage images are among the primary media for communicating and preserving the cultural values of a society. The images represent concrete and abstract content and symbolise the social, economic, political, and cultural values of the society. However, an enormous amount of such values embedded in the images is left unexploited partly due to the absence of methodological and technical solutions to capture, represent, and exploit the latent information. With the emergence of new technologies and availability of cultural heritage images in digital formats, the methodology followed to semantically enrich and utilise such resources become a vital factor in supporting users need. This paper presents a methodology proposed to unearth the cultural information communicated via cultural digital images by applying Artificial Intelligence (AI) technologies (such as Computer Vision (CV) and semantic web technologies). To this end, the paper presents a methodology that enables efficient analysis and enrichment of a large collection of cultural images covering all the major phases and tasks. The proposed method is applied and tested using a case study on cultural image collections from the Europeana platform. The paper further presents the analysis of the case study, the challenges, the lessons learned, and promising future research areas on the topic.
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spelling pubmed-84049202021-10-28 A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies Abgaz, Yalemisew Rocha Souza, Renato Methuku, Japesh Koch, Gerda Dorn, Amelie J Imaging Article Cultural heritage images are among the primary media for communicating and preserving the cultural values of a society. The images represent concrete and abstract content and symbolise the social, economic, political, and cultural values of the society. However, an enormous amount of such values embedded in the images is left unexploited partly due to the absence of methodological and technical solutions to capture, represent, and exploit the latent information. With the emergence of new technologies and availability of cultural heritage images in digital formats, the methodology followed to semantically enrich and utilise such resources become a vital factor in supporting users need. This paper presents a methodology proposed to unearth the cultural information communicated via cultural digital images by applying Artificial Intelligence (AI) technologies (such as Computer Vision (CV) and semantic web technologies). To this end, the paper presents a methodology that enables efficient analysis and enrichment of a large collection of cultural images covering all the major phases and tasks. The proposed method is applied and tested using a case study on cultural image collections from the Europeana platform. The paper further presents the analysis of the case study, the challenges, the lessons learned, and promising future research areas on the topic. MDPI 2021-07-22 /pmc/articles/PMC8404920/ /pubmed/34460757 http://dx.doi.org/10.3390/jimaging7080121 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Abgaz, Yalemisew
Rocha Souza, Renato
Methuku, Japesh
Koch, Gerda
Dorn, Amelie
A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies
title A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies
title_full A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies
title_fullStr A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies
title_full_unstemmed A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies
title_short A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies
title_sort methodology for semantic enrichment of cultural heritage images using artificial intelligence technologies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404920/
https://www.ncbi.nlm.nih.gov/pubmed/34460757
http://dx.doi.org/10.3390/jimaging7080121
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