{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T05:54:06Z","timestamp":1764914046059,"version":"3.46.0"},"reference-count":56,"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\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024YFB3311802"],"award-info":[{"award-number":["2024YFB3311802"]}],"id":[{"id":"10.13039\/501100012166","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.2025.3633770","type":"journal-article","created":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T18:41:09Z","timestamp":1763404869000},"page":"1-14","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic Category Preference Learning: Tackling Long-Tailed Semi-Supervised Segmentation in Remote Sensing"],"prefix":"10.1109","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-6643-5417","authenticated-orcid":false,"given":"Junjun","family":"Li","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5282-7283","authenticated-orcid":false,"given":"Yong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baoqi","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijun","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinze","family":"Liu","sequence":"additional","affiliation":[{"name":"Sydney Smart Technology College, Northeastern University at Qinhuangdao, Qinhuangdao, Hebei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2021.3136100"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2022.3161377"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2017.11.014"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2017.1324976"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3356074"},{"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","article-title":"Semantic image segmentation with deep convolutional nets and fully connected CRFs","author":"Chen","year":"2014","journal-title":"arXiv:1412.7062"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref10","article-title":"Rethinking Atrous convolution for semantic image segmentation","author":"Chen","year":"2017","journal-title":"arXiv:1706.05587"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.02611"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref13","first-page":"1195","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.","volume":"30","author":"Tarvainen"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00423"},{"key":"ref15","article-title":"Semi-supervised semantic segmentation needs strong, high-dimensional perturbations","volume-title":"arXiv:1906.01916","author":"French","year":"2019"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP42928.2021.9506602"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00141"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01269"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.5244\/c.34.154"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00264"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01070"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00812"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108777"},{"key":"ref25","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":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00422"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00699"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00299"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2023.3277203"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2024.3521420"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2023.3272552"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2024.3388199"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2024.3507050"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2975022"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-88013-2_8"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2960224"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58601-0_26"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00348"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00421"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2022.3220755"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2024.3407142"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2024.3376352"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2025.3585489"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2024.3521586"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2025.3571066"},{"key":"ref46","first-page":"14567","article-title":"Distribution aligning refinery of pseudo-label for imbalanced semi-supervised learning","volume-title":"Proc. NIPS","volume":"33","author":"Kim"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01071"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00640"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-022-06247-z"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-43898-1_56"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2023.3332490"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2024.04.010"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02255"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2019.111322"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2022.3152587"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.5194\/isprsannals-i-3-293-2012"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/36\/10807682\/11251067.pdf?arnumber=11251067","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T05:50:03Z","timestamp":1764913803000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11251067\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":56,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2025.3633770","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"type":"print","value":"0196-2892"},{"type":"electronic","value":"1558-0644"}],"subject":[],"published":{"date-parts":[[2025]]}}}