{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T01:16:32Z","timestamp":1780535792168,"version":"3.54.1"},"reference-count":65,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"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":["61806099"],"award-info":[{"award-number":["61806099"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672293"],"award-info":[{"award-number":["61672293"]}],"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":["BK20180790"],"award-info":[{"award-number":["BK20180790"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008045","name":"Nanjing University of Information Science and Technology","doi-asserted-by":"publisher","award":["2243141701077"],"award-info":[{"award-number":["2243141701077"]}],"id":[{"id":"10.13039\/501100008045","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012246","name":"PAPD","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100012246","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1109\/tmm.2019.2900166","type":"journal-article","created":{"date-parts":[[2019,2,18]],"date-time":"2019-02-18T19:21:31Z","timestamp":1550517691000},"page":"2292-2304","source":"Crossref","is-referenced-by-count":35,"title":["Multi-Kernel Coupled Projections for Domain Adaptive Dictionary Learning"],"prefix":"10.1109","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4408-3800","authenticated-orcid":false,"given":"Yuhui","family":"Zheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xilong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8741-8607","authenticated-orcid":false,"given":"Guoqing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3941-1141","authenticated-orcid":false,"given":"Baihua","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1815-2793","authenticated-orcid":false,"given":"Fu","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianwei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.421"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.18"},{"key":"ref33","first-page":"513","article-title":"Domain adaptation for large-scale sentiment classification","author":"glorot","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2745684"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.5244\/C.29.108"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2431440"},{"key":"ref37","first-page":"2096","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.463"},{"key":"ref34","first-page":"1","article-title":"Marginalized denoising autoencoders for domain adaptation","author":"chen","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref60","article-title":"Deep domain confusion: Maximizing for domain invariance","author":"tzeng","year":"2014","journal-title":"arXiv 1412 3474"},{"key":"ref62","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-13560-1_76"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-016-0907-4"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2015.7163133"},{"key":"ref64","doi-asserted-by":"crossref","first-page":"7405","DOI":"10.1109\/TGRS.2016.2601622","article-title":"Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images","volume":"54","author":"gheng","year":"2016","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33765-9_45"},{"key":"ref65","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1109\/TCSVT.2014.2381471","article-title":"Background prior-based salient object detection via deep reconstruction residual","volume":"25","author":"han","year":"2015","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.53"},{"key":"ref2","first-page":"2058","article-title":"Return of frustratingly easy domain adaptation","author":"sun","year":"0","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178934"},{"key":"ref20","first-page":"1079","article-title":"Information-theoretical learning of discriminative adaption","author":"shi","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2704624"},{"key":"ref21","article-title":"Efficient learning for domain-invariant image representation","author":"hoffman","year":"2013","journal-title":"arXiv 1301 3224"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2479405"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2014.2347059"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.95"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.72"},{"key":"ref50","first-page":"2732","article-title":"Fredholm multiple kernel learning for semi-supervised domain adaptation","author":"wang","year":"0","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref51","first-page":"1175","article-title":"Simple and efficient multiple kernel learning by group lasso","author":"xu","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref59","first-page":"647","article-title":"Decaf: A deep convolutional activation feature for generic visual recognition","author":"donahue","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref58","first-page":"7453","article-title":"Domain-shared group-sparse dictionary learning for unsupervised domain adaptation","author":"yang","year":"0","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref57","article-title":"Cross-domain visual recognition via domain adaptive dictionary learning","author":"xu","year":"2018","journal-title":"arXiv 1804 04687"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2014.2306092"},{"key":"ref55","article-title":"Caltech-256 object category data set","author":"griffin","year":"2007"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"ref53","author":"monga","year":"2005","journal-title":"Halftoning Matlab Toolbox"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-012-0584-1"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.151"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2615921"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2011.2179539"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1109\/TMM.2014.2375793","article-title":"Cross-domain feature learning in multimedia","volume":"17","author":"xiao","year":"2015","journal-title":"IEEE Trans Multimedia"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528162"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2785227"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2644866"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2463218"},{"key":"ref17","first-page":"2066","article-title":"Geodesic flow kernel for unsupervised domain adaptation","author":"gong","year":"0","journal-title":"Proc IEEE Conf Comput Vision Pattern Recognit"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.368"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.167"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref3","first-page":"2839","article-title":"Domain adaptation with conditional transferable components","author":"gong","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126344"},{"key":"ref5","first-page":"1785","article-title":"What you saw is not what you get: Domain adaptation using asymmetric kernel transforms","author":"brian","year":"0","journal-title":"Proc IEEE Conf Comput Vision Pattern Recognit"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2014.6836088"},{"key":"ref7","first-page":"213","article-title":"Adapting visual category models to new domains","author":"saenko","year":"0","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.114"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298826"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2324290"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2587119"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.12.001"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.03.005"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2016.07.015"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.04.044"},{"key":"ref44","first-page":"1617","article-title":"Sample-adaptive multiple kernel learning","author":"liu","year":"0","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref43","doi-asserted-by":"crossref","first-page":"1354","DOI":"10.1109\/TPAMI.2013.212","article-title":"Multiple kernel learning for visual object recognition: A review","volume":"36","author":"bucak","year":"2014","journal-title":"IEEE Trans Pattern Anal Mach Intell"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/8811648\/08643808.pdf?arnumber=8643808","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:58:21Z","timestamp":1657745901000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8643808\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9]]},"references-count":65,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tmm.2019.2900166","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9]]}}}