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Moreover, the inspected area is very small. Herein, a simple, inexpensive, and ultrasensitive NDT method for identifying and classifying the geometries of subsurface defects using commercial cameras, digital image correlation software, and object detection (OD) algorithms is developed. Three OD algorithms\u2014Faster region\u2010based convolutional neural network (Faster R\u2010CNN), Mask R\u2010CNN, and you\u2010only\u2010look\u2010once (YOLO)v3\u2014are evaluated for their ability to locate defects and identify defect geometries. Specifically, bounding boxes of two sizes (large and small) are applied to the regions of defect\u2010induced perturbations in strain tensors, which serve as virtual representatives of invisible subsurface defects. The performance of the proposed approach is validated on test datasets of known and unknown defect types. The experimental results confirm that the proposed approach can effectively utilize the surface deformation field information to accurately and reliably locate and identify subsurface defects. The method is nondestructive and low cost, enables real\u2010time detection, is robust against noise\u2010dominated deformation fields, and can be applied to various structural deformations. The method is therefore suitable for multiscale structural health monitoring and characterization of internal defects in materials.<\/jats:p>","DOI":"10.1002\/aisy.202300314","type":"journal-article","created":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T21:35:19Z","timestamp":1697060119000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Identification of Location and Geometry of Invisible Internal Defects in Structures using Deep Learning and Surface Deformation Field"],"prefix":"10.1002","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3362-9369","authenticated-orcid":false,"given":"Suman","family":"Timilsina","sequence":"first","affiliation":[{"name":"School of Nano &amp; Advanced Materials Engineering Kyungpook National University  Kyeongbuk 37224 Republic of Korea"},{"name":"KNU Research Institute of Artificial Intelligent Diagnosis Technology of Multi-scale Organic and Inorganic Structure Kyungpook National University  Kyeongbuk 37224 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seong Min","family":"Jang","sequence":"additional","affiliation":[{"name":"Department of Advanced Science and Technology Convergence Kyungpook National University  Kyeongbuk 37224 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheol Woo","family":"Jo","sequence":"additional","affiliation":[{"name":"School of Nano &amp; Advanced Materials Engineering Kyungpook National University  Kyeongbuk 37224 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong Nam","family":"Kwon","sequence":"additional","affiliation":[{"name":"Department of Digital Platform Korea Institute of Materials Science  Changwon 51508 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kee-Sun","family":"Sohn","sequence":"additional","affiliation":[{"name":"Nanotechnology and Advanced Materials Engineering Sejong University  209 Neungdong ro, Gwangjin-gu Seoul 143-747 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kwang Ho","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Automotive Engineering Kyungpook National University  Kyeongbuk 37224 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1432-8176","authenticated-orcid":false,"given":"Ji Sik","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Nano &amp; Advanced Materials Engineering Kyungpook National University  Kyeongbuk 37224 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,10,9]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-08976-6"},{"key":"e_1_2_9_3_1","unstructured":"R.Girshick J.Donahue T.Darrell J.Malik inProc. 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