DC FieldValueLanguage
dc.contributor.authorJiang, Guimin-
dc.contributor.authorZhu, Pengfei-
dc.contributor.authorSfarra, Stefano-
dc.contributor.authorGargiulo, Gianfranco-
dc.contributor.authorUsamentiaga, Rubén-
dc.contributor.authorKouis, Dimitrios-
dc.contributor.authorYang, Dazhi-
dc.contributor.authorJiang, Tingfei-
dc.contributor.authorGai, Yonggang-
dc.contributor.authorMaldague, Xavier-
dc.contributor.authorZhang, Hai-
dc.date.accessioned2025-03-07T14:04:14Z-
dc.date.available2025-03-07T14:04:14Z-
dc.date.issued2024-11-01-
dc.identifierscopus-85204801280-
dc.identifier.issn1350-4495-
dc.identifier.other85204801280-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/3006-
dc.description.abstractThe demand for non-invasive inspection (NII) is ever-increasing in the field of cultural heritage conservation. NII is a two-step procedure, first of data acquisition and second of defect detection. Stand-alone imaging techniques such as infrared thermography (IRT) are often insufficient for performing a complete remote analysis and diagnosis of historic structures and art pieces that are of very high cultural value. On this point, an emerging optical inspection method, terahertz time-domain spectroscopy (THz-TDS), is herein employed to provide more details of deeper defects. The imaging results from THz-TDS and IRT are compared and analyzed by employing advanced image processing methods. Next, to achieve automatic inspection of the test sample, which is an ancient marquetry, a Faster R-CNN with coordinate attention (Faster R-CNN-CA) is proposed and fitted with data from two different sources. Worth noting is that, in order to populate sufficient data for training, samples are simulated using finite element analysis and finite difference time domain method. The experiments demonstrate that the mean average precision of the Faster R-CNN-CA model improves by 6.09% over the traditional Faster R-CNN model.en_US
dc.language.isoenen_US
dc.relation.ispartofInfrared Physics and Technologyen_US
dc.subjectFaster R-CNNen_US
dc.subjectInfrareden_US
dc.subjectMarquetryen_US
dc.subjectNumerical simulationen_US
dc.subjectTerahertzen_US
dc.subjectThermographyen_US
dc.subjectThermophysical propertiesen_US
dc.titleFaster R-CNN-CA and thermophysical properties of materials: an ancient marquetry inspection based on infrared and terahertz techniquesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.infrared.2024.105563en_US
dc.identifier.scopus2-s2.0-85204801280-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Archival, Library and Information Studiesen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume142en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldEngineering and Technologyen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-5948-9766-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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