Intelligent detection of deterioration in cultural stone heritage

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dc.contributor.authorHatir, M. Ergun
dc.contributor.authorInce, Ismail
dc.contributor.authorKorkanc, Mustafa
dc.date.accessioned2024-02-23T14:12:54Z
dc.date.available2024-02-23T14:12:54Z
dc.date.issued2021
dc.departmentNEÜen_US
dc.description.abstractVision-based periodic examination of the deterioration of stone monuments over time is labour and time intensive. Especially, in cases involving large-scale immovable cultural heritage, the workforce is considerably increased, along with the possibility of occurrence of errors. Any misdiagnoses in the deterioration may cause irreversible structural problems in monuments, and thus, it is necessary to develop alternative examination methods. Computer-vision methods represent an effective solution to eliminate both human errors and difficulties in the field. Therefore, this study aims to adopt the Mask R-CNN algorithm, which is a computer-vision method, to detect and map the deteriorations observed in the Gumus, ler archaeological site and monastery (cracks, discontinuities, contour scaling, missing parts, biological colonization, presence of higher plants, de-posits, efflorescence, and loss of fresco). First, 1740 images were collected from the site, and the model was trained by labelling the distortions in these images according to their types. Later, the model was tested on four outdoor and two indoor views. The developed model achieved an average precision ranging between 91.591% and 100%, and the mean average precision was 98.186%. These results demonstrated that the proposed algorithm can enable mapping to promptly and automatically detect the deterioration in large monuments.en_US
dc.identifier.doi10.1016/j.jobe.2021.102690
dc.identifier.issn2352-7102
dc.identifier.scopus2-s2.0-85105824897en_US
dc.identifier.urihttps://doi.org/10.1016/j.jobe.2021.102690
dc.identifier.urihttps://hdl.handle.net/20.500.12452/12234
dc.identifier.volume44en_US
dc.identifier.wosWOS:000709125900001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofJournal Of Building Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGumus, Ler Monasteryen_US
dc.subjectStone Deteriorationen_US
dc.subjectDeterioration Mapen_US
dc.subjectMaskr-Cnnen_US
dc.titleIntelligent detection of deterioration in cultural stone heritageen_US
dc.typeArticleen_US

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