{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T06:02:51Z","timestamp":1784354571223,"version":"3.55.0"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62176107"],"award-info":[{"award-number":["62176107"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/lsp.2026.3705381","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T20:14:19Z","timestamp":1781813659000},"page":"2645-2649","source":"Crossref","is-referenced-by-count":0,"title":["High-Frequency Information Supported Domain Adaptation for Cross-Domain Object Detection"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7747-1976","authenticated-orcid":false,"given":"Yifan","family":"Yang","sequence":"first","affiliation":[{"name":"School of Computer, Jiangsu University of Science and Technology, Zhenjiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3417-2727","authenticated-orcid":false,"given":"Changbin","family":"Shao","sequence":"additional","affiliation":[{"name":"School of Computer, Jiangsu University of Science and Technology, Zhenjiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4440-0076","authenticated-orcid":false,"given":"Zhibin","family":"Xie","sequence":"additional","affiliation":[{"name":"Ocean College, Jiangsu University of Science and Technology, Zhenjiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1079-8434","authenticated-orcid":false,"given":"Xin","family":"Shu","sequence":"additional","affiliation":[{"name":"School of Computer, Jiangsu University of Science and Technology, Zhenjiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9621-4158","authenticated-orcid":false,"given":"Hualong","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Computer, Jiangsu University of Science and Technology, Zhenjiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3390\/sym17010063"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2016.2603342"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2025.3553426"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2025.3581342"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3217046"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v40i15.38263"},{"key":"ref9","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ganin","year":"2015"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00352"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00712"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00677"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01174"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i16.33885"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00087"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00057"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00408"},{"key":"ref18","first-page":"3040","article-title":"Learning domain adaptive object detection with probabilistic teacher","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chen","year":"2022"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01565"},{"key":"ref20","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107767","article-title":"Structural consistency learning for unsupervised domain adaptive object detection","volume":"191","author":"Jiang","year":"2025","journal-title":"Neural Netw."},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0022"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00414"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-023-01810-0"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-8685-5_2"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00525"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01274"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02283"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3680962"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0291241"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2023.103649"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3390\/s25175363"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58586-0_19"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00270"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01049"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00643"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00015"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989092"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref41","article-title":"Bdd100 k: A diverse driving video database with scalable annotation tooling","author":"Yu","year":"2018"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2938837"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093358"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/97\/11304147\/11570822.pdf?arnumber=11570822","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T05:07:22Z","timestamp":1784351242000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11570822\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/lsp.2026.3705381","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"value":"1070-9908","type":"print"},{"value":"1558-2361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}