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» Maximizing the Number of Independent Labels in the Plane
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ICPR
2006
IEEE
13 years 11 months ago
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure
A novel stereo matching algorithm is proposed that utilizes color segmentation on the reference image and a selfadapting matching score that maximizes the number of reliable corre...
Andreas Klaus, Mario Sormann, Konrad F. Karner
SDM
2009
SIAM
117views Data Mining» more  SDM 2009»
14 years 2 months ago
Spatially Cost-Sensitive Active Learning.
In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Alexander Liu, Goo Jun, Joydeep Ghosh
TNN
2010
155views Management» more  TNN 2010»
13 years 8 hour ago
Incorporating the loss function into discriminative clustering of structured outputs
Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. ...
CCCG
2006
13 years 6 months ago
Polygons Flip Finitely: Flaws and a Fix
Every simple planar polygon can undergo only a finite number of pocket flips before becoming convex. Since Erdos posed this as an open problem in 1935, several independent purport...
Erik D. Demaine, Blaise Gassend, Joseph O'Rourke, ...
ICCV
2005
IEEE
13 years 11 months ago
Robust Point Matching for Two-Dimensional Nonrigid Shapes
Recently, nonrigid shape matching has received more and more attention. For nonrigid shapes, most neighboring points cannot move independently under deformation due to physical co...
Yefeng Zheng, David S. Doermann