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» Feature Correspondence: A Markov Chain Monte Carlo Approach
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CVPR
2007
IEEE
14 years 9 months ago
Compositional Boosting for Computing Hierarchical Image Structures
In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called &q...
Tianfu Wu, Gui-Song Xia, Song Chun Zhu
CVPR
1999
IEEE
13 years 11 months ago
A New Bayesian Framework for Object Recognition
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. This approach provides an effici...
Yuri Boykov, Daniel P. Huttenlocher
BMCBI
2011
13 years 2 months ago
Accurate statistics for local sequence alignment with position-dependent scoring by rare-event sampling
Background: Molecular database search tools need statistical models to assess the significance for the resulting hits. In the classical approach one asks the question how probable...
Stefan Wolfsheimer, Inke Herms, Sven Rahmann, Alex...
TASLP
2008
124views more  TASLP 2008»
13 years 7 months ago
Sparse Linear Regression With Structured Priors and Application to Denoising of Musical Audio
Abstract--We describe in this paper an audio denoising technique based on sparse linear regression with structured priors. The noisy signal is decomposed as a linear combination of...
Cédric Févotte, Bruno Torrésa...
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
14 years 8 days ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel