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SADM
2010
196views more  SADM 2010»
12 years 11 months ago
Bayesian adaptive nearest neighbor
: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...
Ruixin Guo, Sounak Chakraborty
IPMI
2001
Springer
14 years 5 months ago
An Adaptive Level Set Method for Medical Image Segmentation
An efficient adaptive multigrid level set method for front propagation purposes in three dimensional medical image processing and segmentation is presented. It is able to deal with...
Marc Droske, Bernhard Meyer, Martin Rumpf, Carlo S...
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 5 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
CVPR
1996
IEEE
1457views Computer Vision» more  CVPR 1996»
14 years 7 months ago
Edge Detection and Ridge Detection with Automatic Scale Selection
When computing descriptors of image data, the type of information that can be extracted may be strongly dependent on the scales at which the image operators are applied. This arti...
Tony Lindeberg
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
12 years 12 months ago
Model-on-Demand predictive control for nonlinear hybrid systems with application to adaptive behavioral interventions
This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem b...
Naresh N. Nandola, Daniel E. Rivera