{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:05:59Z","timestamp":1780635959604,"version":"3.54.1"},"reference-count":64,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"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":["61771079"],"award-info":[{"award-number":["61771079"]}],"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":["91420201"],"award-info":[{"award-number":["91420201"]}],"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":["61472187"],"award-info":[{"award-number":["61472187"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chongqing Science and Technology Project","award":["cstc2017zdcy-zdzxX0002"],"award-info":[{"award-number":["cstc2017zdcy-zdzxX0002"]}]},{"name":"Chongqing Science and Technology Project","award":["cstc2018jcyjAX0250"],"award-info":[{"award-number":["cstc2018jcyjAX0250"]}]},{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2014CB349303"],"award-info":[{"award-number":["2014CB349303"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Program for Changjiang Scholars"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1109\/tnnls.2019.2899037","type":"journal-article","created":{"date-parts":[[2019,3,26]],"date-time":"2019-03-26T20:47:36Z","timestamp":1553633256000},"page":"3759-3773","source":"Crossref","is-referenced-by-count":105,"title":["Manifold Criterion Guided Transfer Learning via Intermediate Domain Generation"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5305-8543","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanshan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2480-4965","authenticated-orcid":false,"given":"Guang-Bin","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3330-783X","authenticated-orcid":false,"given":"Wangmeng","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4800-832X","authenticated-orcid":false,"given":"Jian","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0034-9013","authenticated-orcid":false,"given":"David","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"2168","article-title":"Robust visual domain adaptation with low-rank reconstruction","author":"jhuo","year":"2012","journal-title":"Proc CVPR"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.59"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0719-3"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.167"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2598679"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.57"},{"key":"ref37","first-page":"530","article-title":"Maximum mean discrepancy for class ratio estimation: Convergence bounds and kernel selection","author":"iyer","year":"2014","journal-title":"Proc ICML"},{"key":"ref36","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"gretton","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126344"},{"key":"ref34","first-page":"2066","article-title":"Geodesic flow kernel for unsupervised domain adaptation","author":"gong","year":"2012","journal-title":"Proc CVPR"},{"key":"ref60","first-page":"2960","article-title":"Unsupervised visual domain adaptation using subspace alignment","author":"fernando","year":"2014","journal-title":"Proc ICCV"},{"key":"ref62","first-page":"2168","article-title":"Robust visual domain adaptation with low-rank reconstruction","author":"chang","year":"2012","journal-title":"Proc CVPR"},{"key":"ref61","first-page":"999","article-title":"Adapting visual category models to new domains","author":"jhuo","year":"2011","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref63","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc NIPS"},{"key":"ref28","first-page":"809","article-title":"Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection","author":"kanamori","year":"2009","journal-title":"Proc NIPS"},{"key":"ref64","article-title":"Columbia object image library (coil-20)","author":"rate","year":"2011"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3089249"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/1291233.1291276"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-58347-1"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2479405"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.318"},{"key":"ref22","author":"ganin","year":"2014","journal-title":"Unsupervised Domain Adaptation by Backpropagation"},{"key":"ref21","first-page":"136","article-title":"Unsupervised domain adaptation with residual transfer networks","author":"long","year":"2016","journal-title":"Proc NIPS"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298629"},{"key":"ref23","first-page":"513","article-title":"A Kernel method for the two-sample-problem","author":"gretton","year":"2007","journal-title":"Proc NIPS"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.116"},{"key":"ref25","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"2015","journal-title":"Proc ICML"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref51","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc NIPS"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.31"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0718-4"},{"key":"ref57","author":"gaidon","year":"2014","journal-title":"Self-learning camera Autonomous adaptation of object detectors to unlabeled video streams"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.79"},{"key":"ref55","first-page":"1391","article-title":"A least-squares approach to direct importance estimation","volume":"10","author":"kanamori","year":"2009","journal-title":"J Mach Learn Res"},{"key":"ref54","article-title":"Iterative projection methods for structured sparsity regularization","author":"rosasco","year":"2009"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1137\/080738970"},{"key":"ref52","first-page":"612","article-title":"Linearized alternating direction method with adaptive penalty for low-rank representation","author":"lin","year":"2011","journal-title":"Proc NIPS"},{"key":"ref10","first-page":"213","article-title":"Adapting visual category models to new domains","author":"saenko","year":"2010","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0696-6"},{"key":"ref12","first-page":"1375","article-title":"Domain transfer SVM for video concept detection","author":"duan","year":"2009","journal-title":"Proc CVPR"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.100"},{"key":"ref14","first-page":"137","article-title":"Analysis of representations for domain adaptation","volume":"19","author":"ben-david","year":"2007","journal-title":"Proc NIPS"},{"key":"ref15","author":"duan","year":"2012","journal-title":"Learning with augmented features for heterogeneous domain adaptation"},{"key":"ref16","first-page":"677","article-title":"Transfer learning via dimensionality reduction","volume":"8","author":"pan","year":"2008","journal-title":"Proc AAAI"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2014.2361936"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298826"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.183"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33709-3_50"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2704624"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.114"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539870"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.249"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2014.131"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995702"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.222"},{"key":"ref45","first-page":"513","article-title":"Domain adaptation for large-scale sentiment classification: A deep learning approach","author":"glorot","year":"2011","journal-title":"Proc ICML"},{"key":"ref48","first-page":"647","article-title":"DeCAF: A deep convolutional activation feature for generic visual recognition","author":"donahue","year":"2014","journal-title":"Proc ICML"},{"key":"ref47","author":"xie","year":"2015","journal-title":"Transfer learning from deep features for remote sensing and poverty mapping"},{"key":"ref42","first-page":"2220","article-title":"Discriminative Kernel transfer learning via l2,1-norm minimization","author":"zhang","year":"2016","journal-title":"Proc IJCNN"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2516952"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.463"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2510498"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/8930649\/08674784.pdf?arnumber=8674784","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T21:14:41Z","timestamp":1657746881000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8674784\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12]]},"references-count":64,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2019.2899037","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12]]}}}