DAML: Domain Adaptation Metric Learning

Search UTSePress Research

Browse

All of UTSePress Research
This Collection
- By Issue Date
- Authors
- Titles
- Subjects

My Account

dc.contributor.author	Geng Bo	en_US
dc.contributor.author	Tao Dacheng	en_US
dc.contributor.author	Xu C	en_US
dc.contributor.editor		en_US
dc.date.accessioned	2012-10-12T03:33:44Z
dc.date.available	2012-10-12T03:33:44Z
dc.date.issued	2011	en_US
dc.identifier	2011001223	en_US
dc.identifier.citation	Geng Bo, Tao Dacheng, and Xu C 2011, 'DAML: Domain Adaptation Metric Learning', IEEE-inst Electrical Electronics Engineers Inc, vol. 20, no. 10, pp. 2980-2989.	en_US
dc.identifier.issn	1057-7149	en_US
dc.identifier.other	C1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/18247
dc.description.abstract	The state-of-the-art metric-learning algorithms cannot perform well for domain adaptation settings, such as cross-domain face recognition, image annotation, etc., because labeled data in the source domain and unlabeled ones in the target domain are drawn	en_US
dc.language		en_US
dc.publisher	IEEE-inst Electrical Electronics Engineers Inc	en_US
dc.relation.isbasedon	http://dx.doi.org/10.1109/TIP.2011.2134107	en_US
dc.title	DAML: Domain Adaptation Metric Learning	en_US
dc.parent	IEEE Transactions On Image Processing	en_US
dc.journal.volume	20	en_US
dc.journal.number	10	en_US
dc.publocation	Piscataway	en_US
dc.identifier.startpage	2980	en_US
dc.identifier.endpage	2989	en_US
dc.cauo.name	FEIT.A/DRsch Ctr Quantum Computat'n & Intelligent Systs	en_US
dc.conference	Verified OK	en_US
dc.for	080100	en_US
dc.personcode	0000072411;111502;0000073389	en_US
dc.percentage	000100	en_US
dc.classification.name	Artificial Intelligence and Image Processing	en_US
dc.classification.type	FOR-08	en_US
dc.edition		en_US
dc.custom		en_US
dc.date.activity		en_US
dc.location.activity		en_US
dc.description.keywords	CLASSIFICATION	en_US
dc.staffid	Peking University	en_US