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» Learning with Tree-Averaged Densities and Distributions
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ICCV
2009
IEEE
15 years 25 days ago
Scene Shape Priors for Superpixel Segmentation
Unsupervised over-segmentation of an image into superpixels is a common preprocessing step for image parsing algorithms. Superpixels are used as both regions of support for feat...
Alastair P. Moore, Simon J. D. Prince, Jonathan Wa...
CVPR
2008
IEEE
14 years 10 months ago
Statistical analysis on Stiefel and Grassmann manifolds with applications in computer vision
Many applications in computer vision and pattern recognition involve drawing inferences on certain manifoldvalued parameters. In order to develop accurate inference algorithms on ...
Pavan K. Turaga, Ashok Veeraraghavan, Rama Chellap...
ICML
2005
IEEE
14 years 8 months ago
Expectation maximization algorithms for conditional likelihoods
We introduce an expectation maximizationtype (EM) algorithm for maximum likelihood optimization of conditional densities. It is applicable to hidden variable models where the dist...
Jarkko Salojärvi, Kai Puolamäki, Samuel ...
INFOCOM
2009
IEEE
14 years 2 months ago
Smart Trend-Traversal: A Low Delay and Energy Tag Arbitration Protocol for Large RFID Systems
—We propose a Smart Trend-Traversal (STT) protocol for RFID tag arbitration, which effectively reduces the collision overhead occurred in the arbitration process. STT, a Query Tr...
Lei Pan, Hongyi Wu
ICCV
2009
IEEE
15 years 25 days ago
Level Set Segmentation with Both Shape and Intensity Priors
We present a new variational level-set-based segmentation formulation that uses both shape and intensity prior information learned from a training set. By applying Bayes’ rule...
Siqi Chen and Richard J. Radke