{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T22:25:07Z","timestamp":1780352707850,"version":"3.54.1"},"reference-count":32,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62073245"],"award-info":[{"award-number":["62073245"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Suzhou Key Industry Technological Innovation-Core Technology Research and Development Program","award":["SGC2021035"],"award-info":[{"award-number":["SGC2021035"]}]},{"name":"Special Funds for Jiangsu Science and Technology Plan","award":["BE2022119"],"award-info":[{"award-number":["BE2022119"]}]},{"name":"Shanghai Municipal Science and Technology Major Project","award":["2021SHZDZX0100"],"award-info":[{"award-number":["2021SHZDZX0100"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Science and Technology Innovation Action Plan","award":["22511104900"],"award-info":[{"award-number":["22511104900"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Instrum. Meas."],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tim.2023.3278293","type":"journal-article","created":{"date-parts":[[2023,5,26]],"date-time":"2023-05-26T17:41:32Z","timestamp":1685122892000},"page":"1-12","source":"Crossref","is-referenced-by-count":13,"title":["Semi-Supervised Bolt Anomaly Detection Based on Local Feature Reconstruction"],"prefix":"10.1109","volume":"72","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7592-2857","authenticated-orcid":false,"given":"Yun","family":"Peng","sequence":"first","affiliation":[{"name":"Robotics and Artificial Intelligence Lab (RAIL), College of Electronics and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0260-6236","authenticated-orcid":false,"given":"Chuangwei","family":"Liu","sequence":"additional","affiliation":[{"name":"Robotics and Artificial Intelligence Lab (RAIL), College of Electronics and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8579-4211","authenticated-orcid":false,"given":"Yi","family":"Yan","sequence":"additional","affiliation":[{"name":"Robotics and Artificial Intelligence Lab (RAIL), College of Electronics and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7107-6577","authenticated-orcid":false,"given":"Nachuan","family":"Ma","sequence":"additional","affiliation":[{"name":"Robotics and Artificial Intelligence Lab (RAIL), College of Electronics and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3486-4176","authenticated-orcid":false,"given":"Deming","family":"Wang","sequence":"additional","affiliation":[{"name":"Robotics and Artificial Intelligence Lab (RAIL), College of Electronics and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7543-0855","authenticated-orcid":false,"given":"Chengju","family":"Liu","sequence":"additional","affiliation":[{"name":"Robotics and Artificial Intelligence Lab (RAIL), College of Electronics and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5644-1188","authenticated-orcid":false,"given":"Qijun","family":"Chen","sequence":"additional","affiliation":[{"name":"Robotics and Artificial Intelligence Lab (RAIL), College of Electronics and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2013.2283741"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1162\/jmlr.2003.3.4-5.993"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TSM.2019.2902657"},{"key":"ref4","article-title":"Sub-image anomaly detection with deep pyramid correspondences","author":"Cohen","year":"2020","journal-title":"arXiv:2005.02357"},{"key":"ref5","article-title":"DFR: Deep feature reconstruction for unsupervised anomaly segmentation","author":"Yang","year":"2020","journal-title":"arXiv:2012.07122"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref8","first-page":"562","article-title":"Deeply-supervised nets","volume-title":"Proc. 18th Int. Conf. Artif. Intell. Statist.","author":"Lee"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636723"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkg509"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/11744023_32"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.177"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00469"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref16","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Tan"},{"key":"ref17","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","volume":"25","author":"Krizhevsky"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00424"},{"key":"ref19","article-title":"Student\u2013teacher feature pyramid matching for anomaly detection","author":"Wang","year":"2021","journal-title":"arXiv:2103.04257"},{"key":"ref20","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015","journal-title":"arXiv:1503.02531"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1967.1053964"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1002\/wics.101"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/2689746.2689747"},{"key":"ref25","article-title":"Improving unsupervised defect segmentation by applying structural similarity to autoencoders","author":"Bergmann","year":"2018","journal-title":"arXiv:1807.02011"},{"key":"ref26","article-title":"Deep unsupervised clustering with Gaussian mixture variational autoencoders","author":"Dilokthanakul","year":"2016","journal-title":"arXiv:1611.02648"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59050-9_12"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2020.3038413"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00982"},{"key":"ref30","article-title":"Towards total recall in industrial anomaly detection","author":"Roth","year":"2021","journal-title":"arXiv:2106.08265"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00188"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00822"}],"container-title":["IEEE Transactions on Instrumentation and Measurement"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/19\/10012124\/10137403.pdf?arnumber=10137403","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T01:10:06Z","timestamp":1705021806000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10137403\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":32,"URL":"https:\/\/doi.org\/10.1109\/tim.2023.3278293","relation":{},"ISSN":["0018-9456","1557-9662"],"issn-type":[{"value":"0018-9456","type":"print"},{"value":"1557-9662","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}