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BMVC
2002
15 years 8 months ago
Randomized RANSAC with T(d, d) test
Many computer vision algorithms include a robust estimation step where model parameters are computed from a data set containing a significant proportion of outliers. The RANSAC al...
Jiri Matas, Ondrej Chum
196
Voted
EDBT
2012
ACM
216views Database» more  EDBT 2012»
13 years 8 months ago
Effectively indexing the multi-dimensional uncertain objects for range searching
The range searching problem is fundamental in a wide spectrum of applications such as radio frequency identification (RFID) networks, location based services (LBS), and global po...
Ying Zhang, Wenjie Zhang, Qianlu Lin, Xuemin Lin
GECCO
2010
Springer
237views Optimization» more  GECCO 2010»
15 years 11 months ago
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noiseless BBOB-2010 testbed
The well-known Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a robust stochastic search algorithm for optimizing functions defined on a continuous search space RD ....
Anne Auger, Dimo Brockhoff, Nikolaus Hansen
BMCBI
2010
137views more  BMCBI 2010»
15 years 6 months ago
Improving pairwise sequence alignment accuracy using near-optimal protein sequence alignments
Background: While the pairwise alignments produced by sequence similarity searches are a powerful tool for identifying homologous proteins - proteins that share a common ancestor ...
Michael L. Sierk, Michael E. Smoot, Ellen J. Bass,...
MICCAI
2006
Springer
16 years 7 months ago
A Landmark-Based Brain Conformal Parametrization with Automatic Landmark Tracking Technique
Abstract. In this paper, we present algorithms to automatically detect and match landmark curves on cortical surfaces to get an optimized brain conformal parametrization. First, we...
Lok Ming Lui, Yalin Wang, Tony F. Chan, Paul M. Th...
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