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» Using Problems to Learn Service-Oriented Computing
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CVPR
2010
IEEE
15 years 12 months ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia
CVPR
2008
IEEE
16 years 8 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
CORR
2010
Springer
171views Education» more  CORR 2010»
15 years 1 months ago
Online Learning in Opportunistic Spectrum Access: A Restless Bandit Approach
We consider an opportunistic spectrum access (OSA) problem where the time-varying condition of each channel (e.g., as a result of random fading or certain primary users' activ...
Cem Tekin, Mingyan Liu
CVPR
2003
IEEE
16 years 8 months ago
Learning epipolar geometry from image sequences
We wish to determine the epipolar geometry of a stereo camera pair from image measurements alone. This paper describes a solution to this problem which does not require a parametr...
Yonatan Wexler, Andrew W. Fitzgibbon, Andrew Zisse...
ICRA
2010
IEEE
101views Robotics» more  ICRA 2010»
15 years 4 months ago
Searching for objects: Combining multiple cues to object locations using a maximum entropy model
— In this paper, we consider the problem of how background knowledge about usual object arrangements can be utilized by a mobile robot to more efficiently find an object in an ...
Dominik Joho, Wolfram Burgard