Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation

Domain adaptation manages to build an effective target classifier or regression model for unlabeled target data by utilizing the well-labeled source data but lying different distributions. Intuitively, to address domain shift problem, it is crucial to learn domain invariant features across domains,...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 27; H. 9; S. 4260 - 4273
Hauptverfasser:	Li, Shuang, Song, Shiji, Huang, Gao, Ding, Zhengming, Wu, Cheng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.09.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptation Adaptation models Classification Data models Domain adaptation Feature extraction Invariants Learning systems Measurement Regression models Representations subspace learning Visual discrimination Visual tasks Visualization
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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