{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T18:25:42Z","timestamp":1771698342397,"version":"3.50.1"},"reference-count":66,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100016319","name":"Key Project of China National Railway Group Company Ltd.","doi-asserted-by":"publisher","award":["K2023T003"],"award-info":[{"award-number":["K2023T003"]}],"id":[{"id":"10.13039\/501100016319","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tgrs.2025.3560724","type":"journal-article","created":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T17:37:06Z","timestamp":1744738626000},"page":"1-14","source":"Crossref","is-referenced-by-count":1,"title":["Semi-Supervised Change Detection With Boundary Refinement Teacher"],"prefix":"10.1109","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-7059-4847","authenticated-orcid":false,"given":"You","family":"Su","sequence":"first","affiliation":[{"name":"School of Software Engineering, Xi’an Jiaotong University, Xi’an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5978-3781","authenticated-orcid":false,"given":"Yonghong","family":"Song","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi’an Jiaotong University, Xi’an, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3111-8079","authenticated-orcid":false,"given":"Xiaomeng","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi’an Jiaotong University, Xi’an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9422-750X","authenticated-orcid":false,"given":"Hao","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Computing, China Academy of Railway Sciences Corporation Ltd., Beijing, China"}]},{"given":"Jingqi","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi’an Jiaotong University, Xi’an, China"}]},{"given":"Zehan","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi’an Jiaotong University, Xi’an, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/rs12101688"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2019.02.017"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrs.2019.02.001"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1080\/014311600210128"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2014.03.001"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2019.2895656"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2012.2210901"},{"key":"ref8","article-title":"Building damage detection in satellite imagery using convolutional neural networks","author":"Xu","year":"2019","journal-title":"arXiv:1910.06444"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3203075"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2024.04.002"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2025.3531646"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3391014"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3300043"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2023.3309854"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2022.3151779"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2572683"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858821"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2960224"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.606"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"},{"key":"ref24","article-title":"Temporal ensembling for semi-supervised learning","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Laine"},{"key":"ref25","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Tarvainen"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00129"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01269"},{"key":"ref28","first-page":"596","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","author":"Sohn"},{"key":"ref29","first-page":"6256","article-title":"Unsupervised data augmentation for consistency training","volume-title":"Proc. NIPS","volume":"33","author":"Xie"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00264"},{"key":"ref31","article-title":"Semi-supervised semantic segmentation needs strong, varied perturbations","volume-title":"Proc. Brit. Mach. Vis. Conf. (BMVC)","author":"French"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.10.008"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207304"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00421"},{"key":"ref35","article-title":"Revisiting consistency regularization for semi-supervised change detection in remote sensing images","author":"Gedara Chaminda Bandara","year":"2022","journal-title":"arXiv:2204.08454"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3247605"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00699"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3370568"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00299"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00262"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3011913"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.3390\/rs14122801"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.jag.2022.103110"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3434427"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3106697"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.3390\/rs14184524"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3300533"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2021.11.005"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2022.3214485"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2024.01.022"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2024.3409072"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2858817"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.3390\/rs12101662"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.06.003"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.02611"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2018.8451102"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS46834.2022.9883686"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2021.3056416"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3095166"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01508"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2959609"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00584"},{"key":"ref65","article-title":"SegFormer: Simple and efficient design for semantic segmentation with transformers","volume-title":"Proc. Neural Inf. Proc. Syst. (NeurIPS)","author":"Xie"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00987"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/36\/10807682\/10965597.pdf?arnumber=10965597","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T17:55:46Z","timestamp":1746467746000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10965597\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":66,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2025.3560724","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}