Semi-supervised cross feature learning for semantic concept detection in videos
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. But a major obstacle to this is the insufficiency of labeled training samples. Multi-view semi-supervised learning algorithms such as co-training may help by incorporati...
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Published in | 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 1; pp. 657 - 663 vol. 1 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
2005
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Subjects | |
Online Access | Get full text |
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