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ML
2006
ACM
142views Machine Learning» more  ML 2006»
14 years 11 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
PAMI
2008
144views more  PAMI 2008»
14 years 11 months ago
Finsler Active Contours
In this paper, we propose an image segmentation technique based on augmenting the conformal (or geodesic) active contour framework with directional information. In the isotropic ca...
John Melonakos, Eric Pichon, Sigurd Angenent, Alle...
PAMI
2006
98views more  PAMI 2006»
14 years 11 months ago
Integral Invariants for Shape Matching
For shapes represented as closed planar contours, we introduce a class of functionals which are invariant with respect to the Euclidean group and which are obtained by performing i...
Siddharth Manay, Daniel Cremers, Byung-Woo Hong, A...
PR
2006
119views more  PR 2006»
14 years 11 months ago
Fingerprint matching by genetic algorithms
Fingerprint matching is still a challenging problem for reliable person authentication because of the complex distortions involved in two impressions of the same finger. In this p...
Xuejun Tan, Bir Bhanu
PRL
2006
139views more  PRL 2006»
14 years 11 months ago
Adaptive Hausdorff distances and dynamic clustering of symbolic interval data
This paper presents a partitional dynamic clustering method for interval data based on adaptive Hausdorff distances. Dynamic clustering algorithms are iterative two-step relocatio...
Francisco de A. T. de Carvalho, Renata M. C. R. de...