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IDA
2002
Springer
13 years 8 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
CP
1998
Springer
14 years 1 months ago
Constraints for Object Recognition in Aerial Images - Handling of Unobserved Features
In this paper we will show how constraint solving methods can be applied for the recognition of buildings in aerial images. Object models are transformed to constraint representati...
Thomas H. Kolbe
JCST
2010
189views more  JCST 2010»
13 years 3 months ago
Formally Analyzing Expected Time Complexity of Algorithms Using Theorem Proving
Probabilistic techniques are widely used in the analysis of algorithms to estimate the computational complexity of algorithms or a computational problem. Traditionally, such analys...
Osman Hasan, Sofiène Tahar
CVPR
1999
IEEE
14 years 10 months ago
Deformable Template and Distribution Mixture-Based Data Modeling for the Endocardial Contour Tracking in an Echographic Sequence
We1 present a new method to shape-based segmentation of deformable anatomical structures in medical images and validate this approach by detecting and tracking the endocardial bor...
Max Mignotte, Jean Meunier
TASLP
2010
117views more  TASLP 2010»
13 years 3 months ago
Speech Enhancement Using Gaussian Scale Mixture Models
This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the fr...
Jiucang Hao, Te-Won Lee, Terrence J. Sejnowski