{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T18:23:41Z","timestamp":1779906221135,"version":"3.53.1"},"reference-count":64,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"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":["61902028"],"award-info":[{"award-number":["61902028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB1003701"],"award-info":[{"award-number":["2018YFB1003701"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB1003700"],"award-info":[{"award-number":["2018YFB1003700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2021,7,1]]},"DOI":"10.1109\/tpami.2020.2964173","type":"journal-article","created":{"date-parts":[[2020,1,7]],"date-time":"2020-01-07T21:13:00Z","timestamp":1578431580000},"page":"2329-2344","source":"Crossref","is-referenced-by-count":138,"title":["Deep Residual Correction Network for Partial Domain Adaptation"],"prefix":"10.1109","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1910-7812","authenticated-orcid":false,"given":"Shuang","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0252-329X","authenticated-orcid":false,"given":"Chi Harold","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuxia","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Wen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4693-5237","authenticated-orcid":false,"given":"Limin","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7251-0988","authenticated-orcid":false,"given":"Gao","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengming","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00288"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_9"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1631\/FITEE.1700774"},{"key":"ref32","article-title":"Deep domain confusion: Maximizing for domain invariance","author":"tzeng","year":"2014","journal-title":"arXiv 1412 3474"},{"key":"ref31","first-page":"3320","article-title":"How transferable are features in deep neural networks?","author":"yosinski","year":"2014","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref30","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":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.463"},{"key":"ref35","first-page":"3934","article-title":"Multi-adversarial domain adaptation","author":"pei","year":"2018","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref34","first-page":"136","article-title":"Unsupervised domain adaptation with residual transfer networks","author":"long","year":"2016","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref60","first-page":"1640","article-title":"Conditional adversarial domain adaptation","author":"long","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.151"},{"key":"ref61","first-page":"4502","article-title":"Fine-grained car detection for visual census estimation","author":"gebru","year":"2017","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref63","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":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.547"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.274"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2839528"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.469"},{"key":"ref1","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref20","first-page":"767","article-title":"Marginalized denoising autoencoders for domain adaptation","author":"chen","year":"2012","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00432"},{"key":"ref21","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2477843"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0692-2"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2538282"},{"key":"ref25","first-page":"601","article-title":"Correcting sample selection bias by unlabeled data","author":"huang","year":"2007","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref50","first-page":"1718","article-title":"Generative moment matching networks","author":"li","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref51","article-title":"Deep manifold traversal: Changing labels with convolutional features","author":"gardner","year":"2015","journal-title":"arXiv 1511 06421"},{"key":"ref59","first-page":"165","article-title":"Label efficient learning of transferable representations acrosss domains and tasks","author":"luo","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref58","first-page":"2066","article-title":"Geodesic flow kernel for unsupervised domain adaptation","author":"gong","year":"2012","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref57","article-title":"Caltech-256 object category dataset","author":"griffin","year":"2007"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2868685"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_16"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553497"},{"key":"ref52","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"arXiv 1502 03167"},{"key":"ref10","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref11","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","author":"sutskever","year":"2014","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00851"},{"key":"ref12","first-page":"1243","article-title":"Convolutional sequence to sequence learning","author":"gehring","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2832198"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-58347-1_1"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"ref17","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","author":"long","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref18","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","author":"ganin","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref19","first-page":"2456","article-title":"Co-training for domain adaptation","author":"chen","year":"2011","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00922"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.634"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.557"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref8","first-page":"562","article-title":"Deeply-supervised nets","author":"lee","year":"2015","journal-title":"Proc 18th Int Conf Artif Intell Statist"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.476"},{"key":"ref49","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.696"},{"key":"ref46","first-page":"343","article-title":"Domain separation networks","author":"bousmalis","year":"2016","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref48","first-page":"513","article-title":"A kernel method for the two-sample-problem","author":"gretton","year":"2007","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.18"},{"key":"ref42","first-page":"2058","article-title":"Return of frustratingly easy domain adaptation","author":"sun","year":"2016","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref41","first-page":"2493","article-title":"Natural language processing (almost) from scratch","volume":"12","author":"collobert","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2599532"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/9448371\/08951442.pdf?arnumber=8951442","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:49:15Z","timestamp":1652194155000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8951442\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":64,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2020.2964173","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,1]]}}}