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dc.contributor.authorLu, Zen_US
dc.contributor.authorFu, Zen_US
dc.contributor.authorXiang, Ten_US
dc.contributor.authorHan, Pen_US
dc.contributor.authorWang, Len_US
dc.contributor.authorGao, Xen_US
dc.date.accessioned2016-06-03T11:46:36Z
dc.date.available2016-03-28en_US
dc.date.issued2017-02en_US
dc.date.submitted2016-06-03T12:42:55.687Z
dc.identifier.issn0162-8828en_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/12661
dc.description.sponsorshipThis work was partially supported by National Natural Science Foundation of China (61573363 and 61573026), 973 Program of China (2014CB340403 and 2015CB352502), the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China (15XNLQ01), IBM Global SUR Award Program, European Research Council FP7 Project SUNNY (313243), and the funding from KAUST.en_US
dc.format.extent486 - 500en_US
dc.relation.ispartofIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCEen_US
dc.rights(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.subjectSemantic segmentationen_US
dc.subjectweakly supervised learningen_US
dc.subjectlabel noise reductionen_US
dc.subjectsparse learningen_US
dc.titleLearning from Weak and Noisy Labels for Semantic Segmentationen_US
dc.typeArticle
dc.rights.holder(c) 2016 IEEE.
dc.identifier.doi10.1109/TPAMI.2016.2552172en_US
pubs.author-urlhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000395555100006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6aen_US
pubs.issue3en_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.volume39en_US
qmul.funderSUNNY: Smart UNattended airborne sensor Network for detection of vessels used for cross border crime and irregular entrY::European Commissionen_US


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