{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T16:24:20Z","timestamp":1781195060358,"version":"3.54.1"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T00:00:00Z","timestamp":1734652800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T00:00:00Z","timestamp":1734652800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100018537","name":"National Science and Technology Major Project","doi-asserted-by":"crossref","award":["J2022-V-0003-0029"],"award-info":[{"award-number":["J2022-V-0003-0029"]}],"id":[{"id":"10.13039\/501100018537","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["12075319"],"award-info":[{"award-number":["12075319"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"DOI":"10.1007\/s10462-024-11073-x","type":"journal-article","created":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T18:14:31Z","timestamp":1734718471000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Damage location and area measurement of aviation functional surface via neural radiance field and improved Yolov8 network"],"prefix":"10.1007","volume":"58","author":[{"given":"Qichun","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haojun","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolong","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yizhen","family":"Yin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junliang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weifeng","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,20]]},"reference":[{"issue":"7","key":"11073_CR1","doi-asserted-by":"publisher","first-page":"126963","DOI":"10.1016\/j.physleta.2020.126963","volume":"385","author":"I Tralle","year":"2021","unstructured":"Tralle I, Chotorlishvili L, Ziba P (2021) Explicit fresnel formulae for the absorbing double-negative metamaterials. Phys Lett A 385(7):126963. https:\/\/doi.org\/10.1016\/j.physleta.2020.126963","journal-title":"Phys Lett A"},{"issue":"1","key":"11073_CR2","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1088\/0964-1726\/13\/1\/013","volume":"13","author":"A Tennantt","year":"2004","unstructured":"Tennantt A, Chambers B (2004) Adaptive radar absorbing structure with PIN diode controlled active frequency selective surface. Smart Mater Struct 13(1):122\u2013125","journal-title":"Smart Mater Struct"},{"key":"11073_CR3","unstructured":"Jocher G, Chaurasia A, Qiu J, Ultralytics YOLO (2024) https:\/\/github.com\/ultralytics\/ultralytics, Accessed: June 6, 2024"},{"key":"11073_CR4","unstructured":"Jie H, Li S, Gang S, Albanie S (2017) Squeeze-and-excitation networks. IEEE Trans Pattern Anal Mach Intell"},{"key":"11073_CR5","doi-asserted-by":"publisher","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez A et al (2017) Attention is all you need, arXiv. https:\/\/doi.org\/10.48550\/arXiv.1706.03762","DOI":"10.48550\/arXiv.1706.03762"},{"key":"11073_CR6","doi-asserted-by":"publisher","unstructured":"Bochkovskiy A, Wang C, Liao H (2020) Yolov4: optimal speed and accuracy of object detection, arXiv preprint. https:\/\/doi.org\/10.48550\/arXiv.2004.10934","DOI":"10.48550\/arXiv.2004.10934"},{"key":"11073_CR7","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M et al (2014) Generative adversarial networks. Adv Neural Inform Proc Syst 2672\u20132680"},{"key":"11073_CR8","doi-asserted-by":"publisher","unstructured":"Dhariwal P, Nichol A (2021) Diffusion models beat gans on image synthesis, arXiv preprint. https:\/\/doi.org\/10.48550\/arXiv.2105.05233","DOI":"10.48550\/arXiv.2105.05233"},{"key":"11073_CR9","doi-asserted-by":"publisher","unstructured":"Mirza M, Osindero S (2014) Conditional Generative Adversarial Networks. arXiv preprint arXiv:1411 1784. https:\/\/doi.org\/10.48550\/arXiv.1411.1784","DOI":"10.48550\/arXiv.1411.1784"},{"key":"11073_CR10","doi-asserted-by":"crossref","unstructured":"Zhu J, Park T, Isola P et al (2017) Unpaired image-to-image translation using cycle-consistent adversarial networks, In: Proceedings of the IEEE International Conference on Computer Vision. 2223\u20132232","DOI":"10.1109\/ICCV.2017.244"},{"key":"11073_CR11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453","author":"T Karras","year":"2019","unstructured":"Karras T, Laine S, Aila T (2019) A Style-based generator architecture for generative adversarial networks. IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR). https:\/\/doi.org\/10.1109\/CVPR.2019.00453","journal-title":"IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"11073_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813","author":"T Karras","year":"2020","unstructured":"Karras T, Laine S, Aittala M, Hellsten J, Lehtinen J, Aila T (2020) Analyzing and improving the image quality of stylegan. IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR). https:\/\/doi.org\/10.1109\/CVPR42600.2020.00813","journal-title":"IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"11073_CR13","doi-asserted-by":"publisher","unstructured":"Rombach R, Blattmann A, Lorenz D, Esser P, Ommer B (2021) High-resolution image synthesis with latent diffusion models, arXiv preprint. https:\/\/doi.org\/10.48550\/arXiv.2112.10752","DOI":"10.48550\/arXiv.2112.10752"},{"issue":"1","key":"11073_CR14","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1145\/3503250","volume":"65","author":"B Mildenhall","year":"2021","unstructured":"Mildenhall B, Srinivasan P, Tancik M et al (2021) Nerf: Representing scenes as neural radiance fields for view synthesis. Commun ACM 65(1):99\u2013106","journal-title":"Commun ACM"},{"key":"11073_CR15","doi-asserted-by":"crossref","unstructured":"Bernhard K, Georgios K, Thomas L (2023) D. George, 3D Gaussian Splatting for Real-Time Radiance Field Rendering. ACM Trans Graphics 42 (4) https:\/\/repo-sam.inria.fr\/fungraph\/3d-gaussian-splatting\/","DOI":"10.1145\/3592433"},{"key":"11073_CR16","doi-asserted-by":"publisher","unstructured":"Xu Q, Xu Z, Philip J, Bi S, Shu Z, Sunkavalli K, Neumann U (2022) Point-NeRF: Point-based Neural Radiance Fields [C]\/\/ Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), : 5428\u20135438. https:\/\/doi.org\/10.1109\/CVPR52688.2022.00536","DOI":"10.1109\/CVPR52688.2022.00536"},{"issue":"4","key":"11073_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3528223.3530127","volume":"41","author":"T M\u00fcller","year":"2022","unstructured":"M\u00fcller T, Evans A, Schied C et al (2022) Instant neural graphics primitives with a multiresolution hash encoding. ACM Trans Graphics (ToG) 41(4):1\u201315","journal-title":"ACM Trans Graphics (ToG)"},{"key":"11073_CR18","unstructured":"Wang P, Liu L, Liu Y et al (2021) Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction. arXiv preprint. arXiv:2106.10689"},{"key":"11073_CR19","doi-asserted-by":"crossref","unstructured":"Barron J, Mildenhall B, Verbin D et al (2023) Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields [C]\/\/ Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), https:\/\/jonbarron.info\/zipnerf\/","DOI":"10.1109\/ICCV51070.2023.01804"},{"key":"11073_CR20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81","author":"R Girshick","year":"2014","unstructured":"Girshick R, Donahue J, Darrell T, Malik J (2014) Rich feature hierarchies for accurate object detection and semantic segmentation. IEEE Comput Soc. https:\/\/doi.org\/10.1109\/CVPR.2014.81","journal-title":"IEEE Comput Soc"},{"key":"11073_CR21","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1312.6229","author":"P Sermanet","year":"2013","unstructured":"Sermanet P, Eigen D, Zhang X, Mathieu M, Fergus R, Lecun Y (2013) Overfeat: integrated recognition, localization and detection using convolutional networks. Eprint Arxiv. https:\/\/doi.org\/10.48550\/arXiv.1312.6229","journal-title":"Eprint Arxiv"},{"key":"11073_CR22","doi-asserted-by":"publisher","unstructured":"Girshick R, Fast R-CNN (2015) International Conference on Computer Vision. IEEE Computer Society. https:\/\/doi.org\/10.1109\/ICCV.2015.169","DOI":"10.1109\/ICCV.2015.169"},{"issue":"6","key":"11073_CR23","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren S, He K, Girshick R, Sun J, Faster R-CNN (2017) towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137\u20131149. https:\/\/doi.org\/10.1109\/TPAMI.2016.2577031","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"11073_CR24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2","volume-title":"SSD: single shot multibox detector","author":"L Wei","year":"2016","unstructured":"Wei L, Dragomir A, Dumitru E, Christian S, Scott R, Cheng-Yang F et al (2016) SSD: single shot multibox detector. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2"},{"key":"11073_CR25","volume-title":"Pelee: a real-time object detection system on mobile devices","author":"R Wang","year":"2018","unstructured":"Wang R, Li X, Ling C (2018) Pelee: a real-time object detection system on mobile devices. Curran Associates Inc, New York"},{"key":"11073_CR26","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1409.1556","author":"K Simonyan","year":"2014","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. Comput Sci. https:\/\/doi.org\/10.48550\/arXiv.1409.1556","journal-title":"Comput Sci"},{"key":"11073_CR27","doi-asserted-by":"publisher","DOI":"10.1145\/3065386","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky A, Sutskever I, Hinton G (2012) Imagenet classification with deep convolutional neural networks. Adv Neural Inf Process Syst. https:\/\/doi.org\/10.1145\/3065386","journal-title":"Adv Neural Inf Process Syst"},{"key":"11073_CR28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90","author":"K He","year":"2016","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR). https:\/\/doi.org\/10.1109\/CVPR.2016.90","journal-title":"IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"11073_CR29","doi-asserted-by":"publisher","unstructured":"Redmon J, Farhadi A (2018) Yolov3: an incremental improvement. arXiv e-prints. https:\/\/doi.org\/10.48550\/arXiv.1804.02767","DOI":"10.48550\/arXiv.1804.02767"},{"key":"11073_CR30","doi-asserted-by":"crossref","unstructured":"Ma X, Dai X, Bai Y, Wang Y, Fu Y (2024) Rewrite the Stars, IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https:\/\/arxiv.org\/abs\/2403.19967","DOI":"10.1109\/CVPR52733.2024.00544"},{"key":"11073_CR31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106","author":"T Lin","year":"2017","unstructured":"Lin T, Dollar P, Girshick R, He K, Hariharan B, Belongie S (2017) Feature pyramid networks for object detection. IEEE Comput Soc. https:\/\/doi.org\/10.1109\/CVPR.2017.106","journal-title":"IEEE Comput Soc"},{"key":"11073_CR32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01079","author":"M Tan","year":"2020","unstructured":"Tan M, Pang R, Le Q (2020) EfficientDet: Scalable and Efficient Object Detection. IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR). https:\/\/doi.org\/10.1109\/CVPR42600.2020.01079","journal-title":"IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"11073_CR33","doi-asserted-by":"publisher","DOI":"10.1080\/17415993.2010.547197","author":"X Wang","year":"2011","unstructured":"Wang X, Feng T, Wei W, Xia H (2011) The failure types of radar absorbing coating and the original place repair techniques. Surf Technol. https:\/\/doi.org\/10.1080\/17415993.2010.547197","journal-title":"Surf Technol"},{"issue":"3","key":"11073_CR34","doi-asserted-by":"publisher","first-page":"183","DOI":"10.3969\/j.issn.1673-6214.2009.03.012","volume":"4","author":"L He","year":"2009","unstructured":"He L, Liu P, Wang X (2009) Degeneration behavior of radar absorbing coatings. Fail Anal Prev 4(3):183\u2013187. https:\/\/doi.org\/10.3969\/j.issn.1673-6214.2009.03.012","journal-title":"Fail Anal Prev"},{"key":"11073_CR35","unstructured":"Zu JAKA 7, https:\/\/www.jaka.com\/productDetails\/JAKA_Zu_7"},{"key":"11073_CR36","unstructured":"A7500CG20 https:\/\/www.irayple.com\/cn\/productDetail\/4434"},{"key":"11073_CR37","unstructured":"MK1628M https:\/\/www.irayple.com\/cn\/productDetail\/3771"},{"key":"11073_CR38","unstructured":"Tzutalin LI (2015) Git code https:\/\/github.com\/tzutalin\/labelImg"},{"key":"11073_CR39","doi-asserted-by":"crossref","unstructured":"Tang L, Zhang H, Xu H, Ma J (2023) Rethinking the necessity of image fusion in high-level vision tasks: a practical infrared and visible image fusion network based on progressive semantic injection and scene fidelity. Inform Fusion 99:101","DOI":"10.1016\/j.inffus.2023.101870"},{"key":"11073_CR40","doi-asserted-by":"publisher","first-page":"2628","DOI":"10.1364\/OE.480816","volume":"31","author":"H Tang","year":"2023","unstructured":"Tang H, Liang S, Yao D, Qiao Y (2023) A visual defect detection for optics lens based on the YOLOv5 -C3CA-SPPF network model. Opt Express 31:2628\u20132643","journal-title":"Opt Express"},{"key":"11073_CR41","doi-asserted-by":"publisher","unstructured":"Li C, Li L, Geng Y et al (2023) YOLOv6 v3.0: A full-scale reloading, arXiv preprint. https:\/\/doi.org\/10.48550\/arXiv.2301.05586","DOI":"10.48550\/arXiv.2301.05586"},{"key":"11073_CR42","doi-asserted-by":"crossref","unstructured":"Wang C, Bochkovskiy A, Liao H (2022) Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. arXiv preprint, arXiv:2207.02696","DOI":"10.1109\/CVPR52729.2023.00721"},{"key":"11073_CR43","doi-asserted-by":"publisher","first-page":"9099","DOI":"10.1109\/TIP.2021.3118953","volume":"30","author":"P Chen","year":"2021","unstructured":"Chen P, Chang M, Hsieh J, Chen Y (2021) Parallel residual Bi-fusion feature pyramid network for accurate single-shot object detection. IEEE Trans Image Process 30:9099\u20139111. https:\/\/doi.org\/10.1109\/TIP.2021.3118953","journal-title":"IEEE Trans Image Process"},{"key":"11073_CR44","doi-asserted-by":"publisher","unstructured":"Xu S, Wang X, Lv W, Chang Q, Cui C, Deng K et al (2022) Pp-yoloe: an evolved version of yolo. arXiv preprint. https:\/\/doi.org\/10.48550\/arXiv.2203.16250","DOI":"10.48550\/arXiv.2203.16250"},{"key":"11073_CR45","doi-asserted-by":"crossref","unstructured":"Zhao Y, Lv W, Xu S et al (2024) DETRs Beat YOLOs on real-time object detection, arXiv preprint. https:\/\/arxiv.org\/abs\/2304.08069","DOI":"10.1109\/CVPR52733.2024.01605"},{"key":"11073_CR46","doi-asserted-by":"crossref","unstructured":"Wang C, Yeh I, Mark Liao H (2024) YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information, arXiv preprint. https:\/\/arxiv.org\/abs\/2402.13616","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"11073_CR47","unstructured":"Wang A, Chen H, Liu L, Chen K, Lin Z, Han J, Ding G (2024) YOLOv10: Real-Time End-to-End Object Detection, arXiv preprint. https:\/\/arxiv.org\/abs\/2405.14458"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-024-11073-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-024-11073-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-024-11073-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T03:45:20Z","timestamp":1738208720000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-024-11073-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,20]]},"references-count":47,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["11073"],"URL":"https:\/\/doi.org\/10.1007\/s10462-024-11073-x","relation":{},"ISSN":["1573-7462"],"issn-type":[{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,20]]},"assertion":[{"value":"13 December 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 December 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"61"}}