{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T16:58:05Z","timestamp":1780419485597,"version":"3.54.1"},"reference-count":57,"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\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61991451"],"award-info":[{"award-number":["61991451"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62302369"],"award-info":[{"award-number":["62302369"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tip.2025.3530788","type":"journal-article","created":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T18:37:01Z","timestamp":1737743821000},"page":"816-827","source":"Crossref","is-referenced-by-count":4,"title":["Local Uncertainty Energy Transfer for Active Domain Adaptation"],"prefix":"10.1109","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9917-0269","authenticated-orcid":false,"given":"Yulin","family":"Sun","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2179-3292","authenticated-orcid":false,"given":"Guangming","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9632-985X","authenticated-orcid":false,"given":"Weisheng","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2067-2763","authenticated-orcid":false,"given":"Xin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University at Albany, Albany, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1410-1534","authenticated-orcid":false,"given":"Le","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7857-0845","authenticated-orcid":false,"given":"Xuemei","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2010.11929"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref7","article-title":"Domain adaptation for visual applications: A comprehensive survey","author":"Csurka","year":"2017","journal-title":"arXiv:1702.05374"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5943"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3028503"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00897"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093390"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00719"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20850"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00814"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00253"},{"issue":"9","key":"ref16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3472291","article-title":"A survey of deep active learning","volume":"54","author":"Ren","year":"2021","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"ref17","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":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3352392"},{"key":"ref19","article-title":"Active learning literature survey","author":"Settles","year":"2009"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01708"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00783"},{"key":"ref22","article-title":"A tutorial on energy-based learning","volume":"1","author":"LeCun","year":"2006","journal-title":"Predicting Structured Data"},{"key":"ref23","first-page":"7404","article-title":"Bridging theory and algorithm for domain adaptation","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","author":"Zhang"},{"key":"ref24","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","volume-title":"Proc. 32nd Int. Conf. Mach. Learn. (ICML)","volume":"2","author":"Ganin"},{"key":"ref25","article-title":"Conditional adversarial domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Long"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17027"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00400"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58589-1_28"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00115"},{"key":"ref31","article-title":"CDTrans: Cross-domain transformer for unsupervised domain adaptation","volume-title":"Proc. ICLR","author":"Xu"},{"key":"ref32","article-title":"Domain adaptation via bidirectional cross-attention transformer","author":"Wang","year":"2022","journal-title":"arXiv:2201.05887"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.2118\/18761-MS"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/584091.584093"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-36618-0_28"},{"key":"ref36","article-title":"Active learning for convolutional neural networks: A core-set approach","volume-title":"Proc. ICLR","author":"Sener"},{"key":"ref37","article-title":"Deep batch active learning by diverse, uncertain gradient lower bounds","volume-title":"Proc. ICLR","author":"Ash"},{"key":"ref38","article-title":"BatchBALD: Efficient and diverse batch acquisition for deep Bayesian active learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Kirsch"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00607"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00622"},{"key":"ref41","first-page":"27","article-title":"Domain adaptation meets active learning","volume-title":"Proc. NAACL HLT Workshop Act. Learn. Nat. Lang. Process.","author":"Rai"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00839"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19827-4_32"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00739"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2014.6889457"},{"key":"ref46","article-title":"Discrepancy-based active learning for domain adaptation","volume-title":"Proc. ICLR","author":"Deheeger"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01916"},{"key":"ref48","article-title":"VisDA: The visual domain adaptation challenge","author":"Peng","year":"2017","journal-title":"arXiv:1710.06924"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_16"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00149"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3455008"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref54","article-title":"ADADELTA: An adaptive learning rate method","author":"Zeiler","year":"2012","journal-title":"arXiv:1212.5701"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729586"},{"issue":"86","key":"ref56","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/83\/10795784\/10851802.pdf?arnumber=10851802","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T05:29:59Z","timestamp":1738301399000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10851802\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/tip.2025.3530788","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}