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» Vessel Scale Selection using MRF Optimization
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CVPR
2010
IEEE
1790views Computer Vision» more  CVPR 2010»
14 years 1 months ago
Data Driven Mean-Shift Belief Propagation For non-Gaussian MRFs
We introduce a novel data-driven mean-shift belief propagation (DDMSBP) method for non-Gaussian MRFs, which often arise in computer vision applications. With the aid of scale sp...
Minwoo Park, S. Kashyap, R. Collins, and Y. Liu
ECCV
1992
Springer
14 years 7 months ago
Boundary Detection in Piecewise Homogeneous Textured Images
We address the problem of scale selection in texture analysis. Two di erent scale parameters, feature scale and statistical scale, are dened. Statistical scale is the size of the r...
Stefano Casadei, Sanjoy K. Mitter, Pietro Perona
ICPR
2004
IEEE
14 years 6 months ago
Large Scale Feature Selection Using Modified Random Mutation Hill Climbing
Feature selection is a critical component of many pattern recognition applications. There are two distinct mechanisms for feature selection, namely the wrapper method and the filt...
Anil K. Jain, Michael E. Farmer, Shweta Bapna
CVPR
2012
IEEE
11 years 7 months ago
Random walks based multi-image segmentation: Quasiconvexity results and GPU-based solutions
We recast the Cosegmentation problem using Random Walker (RW) segmentation as the core segmentation algorithm, rather than the traditional MRF approach adopted in the literature s...
Maxwell D. Collins, Jia Xu, Leo Grady, Vikas Singh
GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
13 years 10 months ago
Solving large scale combinatorial optimization using PMA-SLS
Memetic algorithms have become to gain increasingly important for solving large scale combinatorial optimization problems. Typically, the extent of the application of local search...
Jing Tang, Meng-Hiot Lim, Yew-Soon Ong, Meng Joo E...