{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:19:20Z","timestamp":1740169160635,"version":"3.37.3"},"reference-count":72,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2018YFC0823002"],"award-info":[{"award-number":["2018YFC0823002"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Research and Development Program of Ningxia Hui Autonomous Region","award":["2019BFG02009"],"award-info":[{"award-number":["2019BFG02009"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61801019"],"award-info":[{"award-number":["61801019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.2982034","type":"journal-article","created":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T19:55:33Z","timestamp":1584734133000},"page":"56650-56665","source":"Crossref","is-referenced-by-count":4,"title":["Multi-Adversarial Partial Transfer Learning With Object-Level Attention Mechanism for Unsupervised Remote Sensing Scene Classification"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5453-7389","authenticated-orcid":false,"given":"Peng","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3456-5259","authenticated-orcid":false,"given":"Dezheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0519-169X","authenticated-orcid":false,"given":"Peng","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7909-9012","authenticated-orcid":false,"given":"Xin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7228-7838","authenticated-orcid":false,"given":"Aziguli","family":"Wulamu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8900532"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2964599"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.12.016"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.3390\/rs11141702"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.3390\/rs11131617"},{"key":"ref33","article-title":"OCNet: Object context network for scene parsing","author":"yuan","year":"2018","journal-title":"arXiv 1809 00916"},{"key":"ref32","first-page":"2017","article-title":"Spatial transformer networks","author":"jaderberg","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2608780"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.09.003"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2019.2930724"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2924818"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00326"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref60","first-page":"529","article-title":"Semi-supervised learning by entropy minimization","author":"grandvalet","year":"2004","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00851"},{"key":"ref61","first-page":"136","article-title":"Unsupervised domain adaptation with residual transfer networks","author":"long","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref63","first-page":"213","article-title":"Adapting visual category models to new domains","author":"saenko","year":"2010","journal-title":"Proc 11th Eur Conf Comput Vis"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2731997"},{"key":"ref64","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":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2700322"},{"key":"ref65","article-title":"Equivalence of distance-based and RKHS-based statistics in hypothesis testing","author":"sejdinovic","year":"2012","journal-title":"arXiv 1207 6076"},{"key":"ref66","first-page":"15509","article-title":"Learning representations by maximizing mutual information across views","author":"bachman","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105768"},{"key":"ref67","first-page":"487","article-title":"Learning deep features for scene recognition using places database","author":"zhou","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref68","first-page":"2579","article-title":"Visualizing high-dimensional data using t-SNE","volume":"9","author":"hinton","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.683"},{"key":"ref2","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref1","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","author":"ganin","year":"2015","journal-title":"Proc 32nd Int Conf Mach Learn (ICML)"},{"key":"ref20","first-page":"1","article-title":"Zero-shot learning by convex combination of semantic embeddings","author":"norouzi","year":"2014","journal-title":"Proc Int Conf Learn Represent (ICLR)ICLR"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2015.7301382"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.07.001"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2657778"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2015.2483680"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref50","first-page":"69","article-title":"Unsupervised learning of visual representations by solving jigsaw puzzles","author":"noroozi","year":"2016","journal-title":"Proc 14th Eur Conf Comput Vis"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref59","first-page":"3934","article-title":"Multi-adversarial domain adaptation","author":"pei","year":"2018","journal-title":"Proc 32nd AAAI Conf Artif Intell Innov Appl Artif Intell 8th AAAI Symp Educ Adv Artif Intell"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1145\/1869790.1869829"},{"article-title":"Caltech-256 object category dataset","year":"2007","author":"griffin","key":"ref57"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00352"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.226"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00086"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00152"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2605044"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2484324"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.3390\/rs11222631"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2019.2913512"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/621"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2017.2757264"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2016.12.001"},{"key":"ref16","first-page":"1","article-title":"Incipient winding fault detection and diagnosis for squirrel-cage induction motors equipped on CRH trains","volume":"18","author":"wu","year":"2019","journal-title":"ISA Trans"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2934476"},{"key":"ref18","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2020.107456","article-title":"Structured optimal graph based sparse feature extraction for semi-supervised learning","volume":"170","author":"liu","year":"2020","journal-title":"Signal Process"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2884502"},{"key":"ref4","first-page":"1106","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc 26th Annu Conf Neural Inf Process Syst"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref6","first-page":"59:1","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2675998"},{"key":"ref8","first-page":"1","article-title":"A DIRT-T approach to unsupervised domain adaptation","author":"shu","year":"2018","journal-title":"Proc Int Conf Learn Represent (ICLR)ICLR"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00288"},{"key":"ref49","first-page":"649","article-title":"Colorful image colorization","author":"zhang","year":"2016","journal-title":"Proc 14th Eur Conf Comput Vis"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2810806"},{"key":"ref46","first-page":"481","article-title":"Reducing the inter-speaker variance of CNN acoustic models using unsupervised adversarial multi-task training","author":"t\u00f3th","year":"2019","journal-title":"Proc 21st Int Conf Speech Comput"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2495116"},{"key":"ref48","first-page":"1","article-title":"Unsupervised representation learning by predicting image rotations","author":"gidaris","year":"2018","journal-title":"Proc Int Conf Learn Represent (ICLR)ICLR"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.104975"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682303"},{"key":"ref41","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"2015","journal-title":"Proc 32nd Int Conf Mach Learn (ICML)"},{"key":"ref44","first-page":"7901","article-title":"Modular universal reparameterization: Deep multi-task learning across diverse domains","author":"meyerson","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1001"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09043570.pdf?arnumber=9043570","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T19:55:16Z","timestamp":1643313316000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9043570\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":72,"URL":"https:\/\/doi.org\/10.1109\/access.2020.2982034","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2020]]}}}