Scientific Mapping of Artificial Intelligence (AI) Assisted Applications in Historical Building Conservation
dc.authorscopusid | 58034401800 | |
dc.authorwosid | Kutlu, İzzettin/Jtt-8752-2023 | |
dc.contributor.author | Kutlu, İzzettin | |
dc.contributor.other | Department of Architecture / Mimarlık Bölümü | |
dc.date.accessioned | 2025-06-19T13:45:12Z | |
dc.date.available | 2025-06-19T13:45:12Z | |
dc.date.issued | 2025 | |
dc.department | Artuklu University | en_US |
dc.department-temp | [Kutlu, Izzettin] Mardin Artuklu Univ, Dept Architecture, Mardin, Turkiye | en_US |
dc.description.abstract | The application of developing computer technologies such as artificial intelligence (AI), deep learning (DL), and machine learning (ML) on digital image data can help in monitoring, controlling, and preserving cultural heritage buildings. Defects such as mortar losses, joint damage, discoloration, erosion, cracks, vegetation, leakage, and vandalism seen in cultural heritage buildings negatively affect their structural health. There are a limited number of studies on the use of artificial intelligence and integration at cultural heritage buildings. This study includes the research and bibliometric analysis of existing studies. In the study, structural damage detection techniques performed using AI-assisted image processing techniques are summarized, and deep learning techniques applied, especially in the conservation of heritage sites, are detailed. The study found a significant deficiency in the number of applications and research in this field, particularly within T & uuml;rkiye. AI-assisted digital inspections provide useful data for studies to be conducted in this field and increase the level of confidence in the damage detection of heritage buildings. As a result, today, artificial intelligence, the effective use of which is increasing rapidly, can be integrated into many fields and enables interdisciplinary studies. | en_US |
dc.description.woscitationindex | Science Citation Index Expanded - Arts & Humanities Citation Index | |
dc.identifier.doi | 10.1080/13467581.2025.2505794 | |
dc.identifier.issn | 1346-7581 | |
dc.identifier.issn | 1347-2852 | |
dc.identifier.scopus | 2-s2.0-105005527915 | |
dc.identifier.scopusquality | Q3 | |
dc.identifier.uri | https://doi.org/10.1080/13467581.2025.2505794 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12514/8944 | |
dc.identifier.wos | WOS:001489341700001 | |
dc.identifier.wosquality | Q4 | |
dc.institutionauthor | Kutlu, Izzettin | |
dc.language.iso | en | en_US |
dc.publisher | Taylor & Francis Ltd | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Historical Building | en_US |
dc.subject | Cultural Heritage | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Bibliometrics | en_US |
dc.title | Scientific Mapping of Artificial Intelligence (AI) Assisted Applications in Historical Building Conservation | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
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