A regularized approach for geodesic-based semisupervised multimanifold learning
Geodesic distance, as an essential measurement for data dissimilarity, has been successfully used in manifold learning. However, most geodesic distance-based manifold learning algorithms have two limitations when applied to classification: 1) class information is rarely used in computing the geodesi...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 23(2014), 5 vom: 05. Mai, Seite 2133-47
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| 1. Verfasser: |
Fan, Mingyu
(VerfasserIn) |
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| Weitere Verfasser: |
Zhang, Xiaoqin,
Lin, Zhouchen,
Zhang, Zhongfei,
Bao, Hujun |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2014
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S. |
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