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211
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NIPS
2004
15 years 8 months ago
2004
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
199
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CVPR
2009
IEEE
17 years 1 months ago
2009
IEEE
The ability to constrain the geometry of deformable models for image segmentation can be useful when information about the expected shape or positioning of the objects in a scene i...
204
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CVPR
2004
IEEE
16 years 8 months ago
2004
IEEE
We present Propagation Networks (P-Nets), a novel approach for representing and recognizing sequential activities that include parallel streams of action. We represent each activi...
183
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CVPR
2007
IEEE
16 years 8 months ago
2007
IEEE
We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. The methodology combines kernel pr...
164
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CVPR
2007
IEEE
16 years 8 months ago
2007
IEEE
In object tracking, occlusions significantly undermine the performance of tracking algorithms. Unlike the existing methods that solely depend on the observed target appearance to ...