{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T11:27:05Z","timestamp":1762342025608,"version":"3.37.3"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"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":["62176042","62073059"],"award-info":[{"award-number":["62176042","62073059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100015804","name":"China Computer Federation (CCF)-Baidu Open Fund","doi-asserted-by":"publisher","award":["2021PP15002000"],"award-info":[{"award-number":["2021PP15002000"]}],"id":[{"id":"10.13039\/100015804","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2021B1515140013"],"award-info":[{"award-number":["2021B1515140013"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["ZYGX2021YGCX016"],"award-info":[{"award-number":["ZYGX2021YGCX016"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Circuits Syst. Video Technol."],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1109\/tcsvt.2023.3242614","type":"journal-article","created":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T19:14:47Z","timestamp":1675710887000},"page":"4232-4243","source":"Crossref","is-referenced-by-count":26,"title":["Classification Certainty Maximization for Unsupervised Domain Adaptation"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8631-1915","authenticated-orcid":false,"given":"Zhiqi","family":"Yu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5504-2529","authenticated-orcid":false,"given":"Jingjing","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2993-7142","authenticated-orcid":false,"given":"Lei","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shandong Normal University, Jinan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3456-4993","authenticated-orcid":false,"given":"Ke","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2999-2088","authenticated-orcid":false,"given":"Heng Tao","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2015.2511543"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3060473"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2539541"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2991050"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00400"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2020.2968484"},{"key":"ref10","first-page":"139","article-title":"Generative adversarial nets","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Goodfellow"},{"key":"ref11","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","volume-title":"Proc. 32nd Int. Conf. Mach. Learn.","author":"Ganin"},{"key":"ref12","first-page":"1647","article-title":"Conditional adversarial domain adaptation","volume-title":"Proc. NeuIPS","author":"Long"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350902"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01053"},{"key":"ref16","first-page":"1081","article-title":"Transferability vs. discriminability: Batch spectral penalization for adversarial domain adaptation","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","author":"Chen"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00393"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17027"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3109287"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3062644"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108718"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/tcsvt.2022.3230963"},{"key":"ref23","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","volume-title":"Proc. ICML","author":"Long"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0069"},{"key":"ref25","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Long"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00234"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3081729"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_18"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00261"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413897"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00780"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00503"},{"key":"ref33","first-page":"6028","article-title":"Do we really need to access the source data? Source hypothesis transfer for unsupervised domain adaptation","volume-title":"Proc. 37th Int. Conf. Mach. Learn.","author":"Liang"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00889"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00149"},{"key":"ref36","article-title":"VisDA: The visual domain adaptation challenge","volume-title":"arXiv:1710.06924","author":"Peng","year":"2017"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_16"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"ref39","first-page":"7124","article-title":"Towards accurate model selection in deep unsupervised domain adaptation","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","author":"You"},{"key":"ref40","first-page":"281","article-title":"Semi-supervised learning by entropy minimization","volume":"367","author":"Grandvalet","year":"2005","journal-title":"CAP"},{"key":"ref41","first-page":"1192","article-title":"Adversarial dropout regularization","volume-title":"Proc. ICLR","author":"Saito"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351070"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00151"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00753"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00704"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00701"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00913"},{"key":"ref48","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":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00627"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3124674"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00846"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3070085"}],"container-title":["IEEE Transactions on Circuits and Systems for Video Technology"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/76\/10207864\/10038605.pdf?arnumber=10038605","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,14]],"date-time":"2024-03-14T02:59:00Z","timestamp":1710385140000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10038605\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":52,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tcsvt.2023.3242614","relation":{},"ISSN":["1051-8215","1558-2205"],"issn-type":[{"type":"print","value":"1051-8215"},{"type":"electronic","value":"1558-2205"}],"subject":[],"published":{"date-parts":[[2023,8]]}}}