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ECCV
2008
Springer
15 years 11 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
ACL
2012
13 years 1 days ago
Learning to Find Translations and Transliterations on the Web
In this paper, we present a new method for learning to finding translations and transliterations on the Web for a given term. The approach involves using a small set of terms and ...
Joseph Z. Chang, Jason S. Chang, Jyh-Shing Roger J...
95
Voted
ECCV
2006
Springer
15 years 11 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields
One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with som...
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
88
Voted
PAMI
2008
198views more  PAMI 2008»
14 years 9 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation....
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
76
Voted
IBERAMIA
2004
Springer
15 years 3 months ago
A Case Base Seeding for Case-Based Planning Systems
This paper describes a Case Base Seeding system (CBS) that can be used to seed a case base with some random cases in order to provide minimal conditions for the empirical tests of ...
Flavio Tonidandel, Marcio Rillo