{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T05:49:17Z","timestamp":1776145757691,"version":"3.50.1"},"reference-count":78,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Ningbo Science and Technology Innovation Project","award":["2022Z075"],"award-info":[{"award-number":["2022Z075"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1109\/tits.2026.3658654","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T20:52:07Z","timestamp":1770411127000},"page":"4271-4284","source":"Crossref","is-referenced-by-count":0,"title":["Exploiting Minority Pseudo-Labels for Semi-Supervised Fine-Grained Road Scene Understanding"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1866-6746","authenticated-orcid":false,"given":"Yuting","family":"Hong","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongkang","family":"Wu","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6055-2814","authenticated-orcid":false,"given":"Hui","family":"Xiao","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huazheng","family":"Hao","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojie","family":"Qiu","sequence":"additional","affiliation":[{"name":"Zhejiang Cowain Automation Technology Company Ltd., Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7050-5900","authenticated-orcid":false,"given":"Baochen","family":"Yao","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7445-2638","authenticated-orcid":false,"given":"Chengbin","family":"Peng","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2020.3015866"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.02611"},{"key":"ref3","first-page":"12077","article-title":"SegFormer: Simple and efficient design for semantic segmentation with transformers","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","volume":"34","author":"Xie"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2962073"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3206476"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3179021"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00264"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2023.3236432"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.111179"},{"key":"ref10","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","author":"Tarvainen","year":"2017","journal-title":"arXiv:1703.01780"},{"key":"ref11","first-page":"22106","article-title":"Semi-supervised semantic segmentation via adaptive equalization learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Hu"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00421"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58601-0_26"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00683"},{"key":"ref15","first-page":"3365","article-title":"Learning with pseudo-ensembles","volume-title":"Proc. 28th Conf. Neural Inf. Process. Syst.","volume":"27","author":"Bachman"},{"key":"ref16","doi-asserted-by":"crossref","DOI":"10.5244\/C.34.154","article-title":"Semi-supervised semantic segmentation needs strong, varied perturbations","volume-title":"Proc. Brit. Mach. Vis. Conf. (BMVC)","author":"French"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01269"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207304"},{"issue":"2","key":"ref19","first-page":"896","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","volume":"3","author":"Lee"},{"key":"ref20","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":"ref21","first-page":"1567","article-title":"Learning imbalanced datasets with label-distribution-aware margin loss","volume-title":"Proc. 33rd Int. Conf. Neural Inf. Process. Syst.","author":"Cao"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01100"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01071"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.108886"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.08.052"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00135"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.52202\/068431-0084"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00681"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3207665"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/tits.2025.3577794"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3228380"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20056-4_39"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108837"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49660.2025.10889133"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02300"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01485"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2349"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i11.29084"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i3.25396"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120973"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00699"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00299"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3203630"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00075"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19809-0_38"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00811"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00718"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548353"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00115"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108777"},{"key":"ref54","first-page":"9929","article-title":"Understanding contrastive representation learning through alignment and uniformity on the hypersphere","volume-title":"Proc. 37th Int. Conf. Mach. Learn.","volume":"119","author":"Wang"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/0167-6377(86)90073-8"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88682-2_5"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126343"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00126"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00972"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00423"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00586"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3242819"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3521801"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i6.32631"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.107041"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2025.3586111"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3206496"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.110089"},{"key":"ref73","article-title":"PseudoSeg: Designing pseudo labels for semantic segmentation","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Zou"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00422"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01484"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01091"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01523"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00092"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6979\/11480687\/11373764.pdf?arnumber=11373764","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T05:03:22Z","timestamp":1776143002000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11373764\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":78,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tits.2026.3658654","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]}}}