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ICCV
2009
IEEE
15 years 4 months ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu
ICCV
2009
IEEE
15 years 4 months ago
Incremental Multiple Kernel Learning for object recognition
A good training dataset, representative of the test images expected in a given application, is critical for ensuring good performance of a visual categorization system. Obtaining ...
Aniruddha Kembhavi, Behjat Siddiquie, Roland Miezi...
CDC
2010
IEEE
106views Control Systems» more  CDC 2010»
15 years 1 months ago
Optimal cross-layer wireless control policies using TD learning
We present an on-line crosslayer control technique to characterize and approximate optimal policies for wireless networks. Our approach combines network utility maximization and ad...
Sean P. Meyn, Wei Chen, Daniel O'Neill
TON
2010
126views more  TON 2010»
15 years 1 months ago
MAC Scheduling With Low Overheads by Learning Neighborhood Contention Patterns
Aggregate traffic loads and topology in multi-hop wireless networks may vary slowly, permitting MAC protocols to `learn' how to spatially coordinate and adapt contention patte...
Yung Yi, Gustavo de Veciana, Sanjay Shakkottai
CVPR
2007
IEEE
16 years 8 months ago
Monocular and Stereo Methods for AAM Learning from Video
The active appearance model (AAM) is a powerful method for modeling deformable visual objects. One of the major drawbacks of the AAM is that it requires a training set of pseudo-d...
Jason Saragih, Roland Göcke