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» Learning How to Propagate Using Random Probing
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ICIP
2008
IEEE
14 years 10 months ago
Efficient BP stereo with automatic paramemeter estimation
In this paper, we propose a series of techniques to enhance the computational performance of existing Belief Propagation (BP) based stereo matching that relies on automatic estima...
Shafik Huq, Andreas Koschan, Besma R. Abidi, Mongi...
ACCV
2010
Springer
13 years 4 months ago
Four Color Theorem for Fast Early Vision
Recent work on early vision such as image segmentation, image restoration, stereo matching, and optical flow models these problems using Markov Random Fields. Although this formula...
Radu Timofte, Luc J. Van Gool
CORR
2010
Springer
171views Education» more  CORR 2010»
13 years 3 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
2009
IEEE
15 years 4 months ago
Learning color and locality cues for moving object detection and segmentation
This paper presents an algorithm for automatically detecting and segmenting a moving object from a monocular video. Detecting and segmenting a moving object from a video with limit...
Feng Liu (University of Wisconsin-Madison), Michae...
UAI
2004
13 years 10 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani