Combining reconstructive and discriminative subspace methods for robust classification and regression by subsampling
Linear subspace methods that provide sufficient reconstruction of the data, such as PCA, offer an efficient way of dealing with missing pixels, outliers, and occlusions that often appear in the visual data. Discriminative methods, such as LDA, which, on the other hand, are better suited for classifi...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 28(2006), 3 vom: 09. März, Seite 337-50 |
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| Format: | Aufsatz |
| Sprache: | English |
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2006
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Evaluation Study Journal Article Research Support, Non-U.S. Gov't |