{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T06:34:09Z","timestamp":1757313249432,"version":"3.37.3"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:00:00Z","timestamp":1687996800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:00:00Z","timestamp":1687996800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s11042-023-16061-x","type":"journal-article","created":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T05:01:41Z","timestamp":1688014901000},"page":"12403-12424","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Joint attention mechanism with dynamic kernel for yolov5 mobile wireless charging coil surface defect identification"],"prefix":"10.1007","volume":"83","author":[{"given":"Zhao","family":"Wei","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8615-2034","authenticated-orcid":false,"given":"Tingting","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,29]]},"reference":[{"unstructured":"Bochovskiy A, Wang C, Liao HM (2020) YOLOV4:Optimal speed and accuracy of object detection. arXiv preprint arXiv2004.10934","key":"16061_CR1"},{"issue":"5","key":"16061_CR2","doi-asserted-by":"publisher","first-page":"1483","DOI":"10.1109\/TPAMI.2019.2956516","volume":"43","author":"Z Cai","year":"2019","unstructured":"Cai Z, Vasconcelos N (2019) Cascade R-CNN: high quality object detection and instance segmentation. IEEE transactions on pattern analysis and machine intelligence 43(5):1483\u20131498","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A et al (2021) An image is worth 16x16 words: Transformers for image recognition at scale. In International Conference on Learning Representations","key":"16061_CR3"},{"issue":"2","key":"16061_CR4","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2010","unstructured":"Everingham M, Gool LV, Williams CK et al (2010) The pascal visual object classes (voc) challeng e. IJCV 88(2):303\u2013338","journal-title":"IJCV"},{"unstructured":"Ge Z, Liu S, Wang F, Li Z et al (2021) Yolox: Exceeding yolo series in 2021. arXiv preprint arXiv:2107.08430","key":"16061_CR5"},{"doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S et al (2016) Deep Residual Learning for Image Recognition. IEEE Conference on Computer Vision & Pattern Recognition","key":"16061_CR6","DOI":"10.1109\/CVPR.2016.90"},{"issue":"9","key":"16061_CR7","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"KM He","year":"2014","unstructured":"He KM, Zhang XY, Ren SQ (2014) Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition. IEEE Trans Pattern Anal Mach Intell 37(9):1904\u201316","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. Proceedings of the IEEE conference on computer vision and pattern recognition","key":"16061_CR8","DOI":"10.1109\/CVPR.2018.00745"},{"doi-asserted-by":"publisher","unstructured":"Jocher G, Stoken A, Borovec J et al. YOLOV5[EB\/OL]. https:\/\/doi.org\/10.5281\/zenodo.4154370","key":"16061_CR9","DOI":"10.5281\/zenodo.4154370"},{"issue":"7","key":"16061_CR10","doi-asserted-by":"publisher","first-page":"0","DOI":"10.1109\/TPAMI.2002.1017616","volume":"24","author":"T Kanungo","year":"2002","unstructured":"Kanungo T, Mount DM, Netanyahu NS et al (2002) An efficient k-means clusterung algorithm: analyssis and implementation. IEEE Trans Pattern Anal Mach Intell 24(7):0\u2013892","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"16061_CR11","volume-title":"Research on rotor winding detection method and technology based on computer vision [D]","author":"HR Lin","year":"2017","unstructured":"Lin HR (2017) Research on rotor winding detection method and technology based on computer vision [D]. Southeast University, Jiangsu"},{"doi-asserted-by":"crossref","unstructured":"Lin TY, Dollar P, Girshick R et al (2017) Feature pyramid networks for object detection. In IEEE Conference on Computer Vision and Pattern Recognition, pp. 2117\u20132125","key":"16061_CR12","DOI":"10.1109\/CVPR.2017.106"},{"doi-asserted-by":"crossref","unstructured":"Liu Z,Lin Y T, Hu H et al (2021) Swin Transformer: Hierarchical Vision Transformer using Shifted Windows. arXiv preprint arXiv: 2103.14030","key":"16061_CR13","DOI":"10.1109\/ICCV48922.2021.00986"},{"doi-asserted-by":"crossref","unstructured":"Liu S,Qi L,Qin HF et al (2018) Path aggregation network for instance segmentation. In IEEE Conference on Computer Vision and Pattern Recognition, pp 8759\u20138768","key":"16061_CR14","DOI":"10.1109\/CVPR.2018.00913"},{"unstructured":"Mehta S, Rastegari M (2021) MobileViT:Light-weight, General-purpose, and Mobile-friendly Vision Transformer. arXiv preprint arXiv: 2110.02178","key":"16061_CR15"},{"doi-asserted-by":"crossref","unstructured":"Misra D, Nalamada T, Arasanipalai AU et al (2020) Rotate to Attend: Convolutional Triplet Attention Module. arXiv preprint arXiv: 2010.03045","key":"16061_CR16","DOI":"10.1109\/WACV48630.2021.00318"},{"key":"16061_CR17","volume-title":"Research on stator coil defect detection algorithm based on deep learning[D]","author":"LY Ni","year":"2020","unstructured":"Ni LY (2020) Research on stator coil defect detection algorithm based on deep learning. Shandong University of science and technology, Shandong"},{"key":"16061_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2022.106780","volume":"194","author":"J Qi","year":"2022","unstructured":"Qi J, Liu X, Liu K et al (2022) An improved YOLOv5 model based on visual attention mechanism: Application to recognition of tomato virus disease. Comput Electron Agric 194:106780","journal-title":"Comput Electron Agric"},{"issue":"5","key":"16061_CR19","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1109\/JAS.2023.123456","volume":"10","author":"Z Qin","year":"2023","unstructured":"Qin Z, Lu X, Nie X, Liu D, Yin Y, Wang W (2023) Coarse-to-Fine Video Instance Segmentation With Factorized Conditional Appearance Flows. IEEE\/CAA Journal of Automatica Sinica 10(5):1192\u20131208. https:\/\/doi.org\/10.1109\/JAS.2023.123456","journal-title":"IEEE\/CAA Journal of Automatica Sinica"},{"unstructured":"Redmon J, Farhadi A (2018) YOLOV3: An Incremental Improvement. arXiv preprint arXiv: 1804.02767","key":"16061_CR20"},{"doi-asserted-by":"crossref","unstructured":"Girshick R (2015) Fast r-cnn[C]\/\/Proceedings of the IEEE international conference on computer vision 1440\u20131448","key":"16061_CR21","DOI":"10.1109\/ICCV.2015.169"},{"issue":"3","key":"16061_CR22","doi-asserted-by":"publisher","first-page":"608","DOI":"10.3390\/rs14030608","volume":"14","author":"C Shi","year":"2022","unstructured":"Shi C, Liao D, Zhang T et al (2022) Hyperspectral image classification based on 3D coordination attention mechanism network. Remote Sensing 14(3):608","journal-title":"Remote Sensing"},{"doi-asserted-by":"crossref","unstructured":"Tan M, Pang R, Le QV (2020) Efficientdet: Scalable and efficient object detection[C]\/\/Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition 10781\u201310790","key":"16061_CR23","DOI":"10.1109\/CVPR42600.2020.01079"},{"issue":"1","key":"16061_CR24","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1038\/s41598-022-27266-9","volume":"13","author":"Z Ullah","year":"2023","unstructured":"Ullah Z, Usman M, Latif S et al (2023) Densely attention mechanism based network for COVID-19 detection in chest X-rays. Sci Rep 13(1):261","journal-title":"Sci Rep"},{"doi-asserted-by":"crossref","unstructured":"Wang J, Chen K, Xu R et al (2019) Carafe: Content-aware reassembly of features. In The IEEE International Conference on Computer Vision (ICCV)","key":"16061_CR25","DOI":"10.1109\/ICCV.2019.00310"},{"doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee JY et al (2018) Cbam: Convolutional block attention module. In Proceedings of the European conference on computer vision (ECCV), pp. 3\u201319","key":"16061_CR26","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"16061_CR27","volume-title":"Research on rotor winding qualification detection algorithm based on anti neural network and attention mechanism[D]","author":"S Yan","year":"2020","unstructured":"Yan S (2020) Research on rotor winding qualification detection algorithm based on anti neural network and attention mechanism. Southeast University, Jiangsu"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-16061-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-16061-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-16061-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T09:48:56Z","timestamp":1704880136000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-16061-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,29]]},"references-count":27,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["16061"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-16061-x","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2023,6,29]]},"assertion":[{"value":"10 June 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 May 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}