{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T15:32:03Z","timestamp":1778599923482,"version":"3.51.4"},"reference-count":69,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"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 Plan of China","doi-asserted-by":"publisher","award":["2024YFE0202700"],"award-info":[{"award-number":["2024YFE0202700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2433216"],"award-info":[{"award-number":["U2433216"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20231337"],"award-info":[{"award-number":["BK20231337"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Jiangsu Higher Education Institutions of China","award":["24KJB520032"],"award-info":[{"award-number":["24KJB520032"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1109\/tnnls.2025.3561401","type":"journal-article","created":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T13:03:56Z","timestamp":1746536636000},"page":"17365-17379","source":"Crossref","is-referenced-by-count":28,"title":["Multilevel Distribution Alignment for Multisource Universal Domain Adaptation"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6903-8996","authenticated-orcid":false,"given":"Liangbo","family":"Ning","sequence":"first","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4855-5924","authenticated-orcid":false,"given":"Zuowei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3180-7347","authenticated-orcid":false,"given":"Weiping","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Nantong University, Nantong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0862-9941","authenticated-orcid":false,"given":"Dian","family":"Shao","sequence":"additional","affiliation":[{"name":"Unmanned System Research Institute, Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yining","family":"Zhu","sequence":"additional","affiliation":[{"name":"Computer Science Department, Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2025.3539358"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2025.3529979"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3431283"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3362948"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3151683"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3201623"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20850"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3152052"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015989"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3179805"},{"key":"ref11","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","volume-title":"Proc. 32nd Int. Conf. Mach. Learn.","volume":"37","author":"Long"},{"key":"ref12","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","volume-title":"Proc. 32nd Int. Conf. Mach. Learn. (ICML)","author":"Ganin"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3145034"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00419"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3214930"},{"key":"ref16","first-page":"16755","article-title":"Unknown-aware domain adversarial learning for open-set domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Jang"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28765"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00963"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01566"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i6.20575"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3376449"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2988928"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.12.022"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3194533"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00851"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2964173"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01228-1_10"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00304"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58555-6_34"},{"key":"ref30","first-page":"16282","article-title":"Universal domain adaptation through self supervision","volume-title":"Proc. NIPS","volume":"33","author":"Saito"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108238"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2025.3548894"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3111034"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3179021"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.07.010"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_35"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00503"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3029948"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00754"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3203220"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01102"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01765"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.5555\/2946645.2946704"},{"key":"ref45","first-page":"1989","article-title":"CyCADA: Cycle-consistent adversarial domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hoffman"},{"key":"ref46","first-page":"1647","article-title":"Conditional adversarial domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Long"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3116210"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00288"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_9"},{"key":"ref50","first-page":"6468","article-title":"Progressive graph learning for open-set domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Luo"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.88"},{"key":"ref52","article-title":"Learning factorized representations for open-set domain adaptation","author":"Baktashmotlagh","year":"2018","journal-title":"arXiv:1805.12277"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00283"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109632"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.01.009"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2018.2800014"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_16"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1097\/00003643-201406001-00333"},{"key":"ref62","first-page":"1","article-title":"Learning Wasserstein embeddings","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Courty"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2868685"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/3711896.3736555"},{"key":"ref65","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"139","author":"Radford"},{"key":"ref66","first-page":"12888","article-title":"BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2022.02.027"},{"key":"ref68","first-page":"1","article-title":"Deep inside convolutional networks: Visualising image classification models and saliency maps","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Simonyan"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5962385\/11151745\/10988896.pdf?arnumber=10988896","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,5]],"date-time":"2025-09-05T18:24:57Z","timestamp":1757096697000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10988896\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":69,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2025.3561401","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9]]}}}