{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,7]],"date-time":"2026-06-07T15:59:57Z","timestamp":1780847997855,"version":"3.54.1"},"reference-count":65,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2022A1515011370"],"award-info":[{"award-number":["2022A1515011370"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62276103"],"award-info":[{"award-number":["62276103"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovation Team Project of General Colleges and Universities in Guangdong Province","award":["2023KCXTD002"],"award-info":[{"award-number":["2023KCXTD002"]}]},{"name":"Research and Development Project on Key Technologies for Intelligent Sensing and Analysis of Urban Events Based on Low-Altitude Drones","award":["2024BQ010011"],"award-info":[{"award-number":["2024BQ010011"]}]},{"name":"Philosophy and Social Science Project of Guangdong Province","award":["GD23SJZ09"],"award-info":[{"award-number":["GD23SJZ09"]}]},{"name":"Fundamental Research Funds for the Central Universities JLU","award":["93K172024K24"],"award-info":[{"award-number":["93K172024K24"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Emerg. Top. Comput. Intell."],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1109\/tetci.2025.3572133","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T14:03:52Z","timestamp":1748873032000},"page":"4175-4190","source":"Crossref","is-referenced-by-count":1,"title":["Prototype Combination for Multi-Source Unsupervised Domain Adaptation"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7141-7434","authenticated-orcid":false,"given":"Min","family":"Huang","sequence":"first","affiliation":[{"name":"School of Software Engineering, South China University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2666-7696","authenticated-orcid":false,"given":"Zifeng","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Software Engineering, South China University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1617-4147","authenticated-orcid":false,"given":"Han","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Software Engineering, South China University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7193-3786","authenticated-orcid":false,"given":"Chang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Software Engineering, South China University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7831-6643","authenticated-orcid":false,"given":"Liuqi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Operation and Maintenance Center of Information and Communication, CSG EHV Power Transmission Company, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2253-0566","authenticated-orcid":false,"given":"Ziyan","family":"Feng","sequence":"additional","affiliation":[{"name":"Operation and Maintenance Center of Information and Communication, CSG EHV Power Transmission Company, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3353612"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3356163"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3355819"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.01.024"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3358103"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2651-7"},{"key":"ref7","first-page":"3320","article-title":"How transferable are features in deep neural networks?","volume-title":"Proc. Adv. Neural Inf. Proces. Syst.","volume":"27","author":"Yosinski","year":"2014"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9780262170055.001.0001"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109974"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58598-3_43"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICAISS55157.2022.10011051"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.459"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3327962"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102457"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2023.104431"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107912"},{"key":"ref17","first-page":"1647","article-title":"Conditional adversarial domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Long","year":"2018"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2023.3234548"},{"key":"ref19","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","volume-title":"Proc. Int. Conf. Machin. Learn.","author":"Ganin","year":"2015"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2022.3221129"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11784"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00400"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3172372"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015989"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00149"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6997"},{"key":"ref27","first-page":"8568","article-title":"Adversarial multiple source domain adaptation","volume-title":"Proc. Adv. Neural Inf. Proces. Syst.","volume":"31","author":"Zhao","year":"2018"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00172"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01223"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00234"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2022.10.015"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00347"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3358172"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2022.03.031"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2021.3055873"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00875"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"key":"ref39","first-page":"1041","article-title":"Domain adaptation with multiple sources","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"21","author":"Mansour","year":"2008"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247924"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00417"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00637"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58517-4_23"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2022.3207457"},{"issue":"1","key":"ref47","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"Gretton","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.591"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247911"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.5555\/2946645.2946704"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/34.291440"},{"issue":"5","key":"ref53","article-title":"Reading digits in natural images with unsupervised feature learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"2011","author":"Yuval","year":"2011"},{"key":"ref54","article-title":"Automatic differentiation in pytorch","author":"Paszke","year":"2017","journal-title":"NIPS Workshop Autodiff"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58568-6_36"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01085"},{"key":"ref57","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Long","year":"2015"},{"key":"ref58","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Long","year":"2017"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_35"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240512"},{"key":"ref63","article-title":"The magic number 30: Why sample size is often considered sufficient","author":"Brownlee","year":"2024"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.2307\/2331554"},{"issue":"86","key":"ref65","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Emerging Topics in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7433297\/11267152\/11020760.pdf?arnumber=11020760","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T18:30:45Z","timestamp":1764095445000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11020760\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":65,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tetci.2025.3572133","relation":{},"ISSN":["2471-285X"],"issn-type":[{"value":"2471-285X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12]]}}}