Transfer learning for image classification with sparse prototype representations
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer learning which exploits available unlabeled data and an arbitrary kernel function; we form a representation based on kerne...
| Main Authors: | , , |
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| Other Authors: | |
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2008
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/40797 |