{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T13:05:11Z","timestamp":1780319111109,"version":"3.54.1"},"reference-count":46,"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\/501100012166","name":"Grants of the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020AAA0108302"],"award-info":[{"award-number":["2020AAA0108302"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009019","name":"Shenzhen University 2035 Program for Excellent Research","doi-asserted-by":"publisher","award":["00000224"],"award-info":[{"award-number":["00000224"]}],"id":[{"id":"10.13039\/501100009019","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Research Fund from Guangdong Laboratory of Artificial Intelligence and Digital Economy"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Instrum. Meas."],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tim.2023.3320746","type":"journal-article","created":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T17:50:52Z","timestamp":1696269052000},"page":"1-13","source":"Crossref","is-referenced-by-count":20,"title":["EEE-Net: Efficient Edge Enhanced Network for Surface Defect Detection of Glass"],"prefix":"10.1109","volume":"72","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8243-9468","authenticated-orcid":false,"given":"Yongqi","family":"Chen","sequence":"first","affiliation":[{"name":"Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4155-3010","authenticated-orcid":false,"given":"Jiawei","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Automation, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5996-925X","authenticated-orcid":false,"given":"Jiayu","family":"Lei","sequence":"additional","affiliation":[{"name":"Meizhou Academy of Medical Sciences, Meizhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6656-8024","authenticated-orcid":false,"given":"Deyu","family":"Zeng","sequence":"additional","affiliation":[{"name":"College of Mechatronics and Control Engineering and the College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2115-8670","authenticated-orcid":false,"given":"Zongze","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4857-6810","authenticated-orcid":false,"given":"Changsheng","family":"Chen","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","first-page":"5455","article-title":"Visual saliency based on multiscale deep features","author":"li","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref35","first-page":"1243","article-title":"Convolutional sequence to sequence learning","author":"gehring","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref15","first-page":"1","article-title":"An image is worth 16?16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2021","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.12509"},{"key":"ref36","first-page":"213","article-title":"End-to-end object detection with transformers","author":"carion","year":"2020","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108396"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747311"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3015868"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3004469"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2878966"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3126847"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.addma.2021.101965"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.compind.2022.103689"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-022-0274-8"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-007-0090-8"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.11.041"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1002\/int.22974"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3124814"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.4028\/www.scientific.net\/AMM.437.362"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2022.3186054"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00717"},{"key":"ref26","article-title":"CrossFormer: A versatile vision transformer hinging on cross-scale attention","author":"wang","year":"2022","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref25","first-page":"6000","article-title":"Attention is all you need","volume":"30","author":"vaswani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmapro.2020.12.067"},{"key":"ref42","first-page":"10326","article-title":"K-Net: Towards unified image segmentation","volume":"34","author":"zhang","year":"2021","journal-title":"Proc NeurIPS"},{"key":"ref41","first-page":"801","article-title":"Encoder&#x2013;decoder with atrous separable convolution for semantic image segmentation","author":"chen","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1007\/s10845-019-01476-x","article-title":"Segmentation-based deep-learning approach for surface-defect detection","volume":"31","author":"tabernik","year":"2020","journal-title":"J Intell Manuf"},{"key":"ref44","first-page":"9355","article-title":"Twins: Revisiting the design of spatial attention in vision transformers","volume":"34","author":"chu","year":"2021","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3092510"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01167"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412092"},{"key":"ref27","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","author":"touvron","year":"2021","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00711"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s40684-021-00343-6"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.10.030"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3053987"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.106530"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2019.2899478"},{"key":"ref6","first-page":"3523","article-title":"Image segmentation using deep learning: A survey","volume":"44","author":"minaee","year":"2022","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-020-01710-x"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"}],"container-title":["IEEE Transactions on Instrumentation and Measurement"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/19\/10012124\/10269087.pdf?arnumber=10269087","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T19:15:34Z","timestamp":1699298134000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10269087\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/tim.2023.3320746","relation":{},"ISSN":["0018-9456","1557-9662"],"issn-type":[{"value":"0018-9456","type":"print"},{"value":"1557-9662","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}