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» Robust Classification with Context-Sensitive Features
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NIPS
2004
13 years 9 months ago
Outlier Detection with One-class Kernel Fisher Discriminants
The problem of detecting "atypical objects" or "outliers" is one of the classical topics in (robust) statistics. Recently, it has been proposed to address this...
Volker Roth
APIN
2010
108views more  APIN 2010»
13 years 7 months ago
A low variance error boosting algorithm
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...
Ching-Wei Wang, Andrew Hunter
INFORMATICALT
2008
104views more  INFORMATICALT 2008»
13 years 7 months ago
An Efficient Technique to Detect Visual Defects in Particleboards
This paper is concerned with the problem of image analysis based detection of local defects embedded in particleboard surfaces. Though simple, but efficient technique developed is ...
Jonas Guzaitis, Antanas Verikas
VLSISP
2002
124views more  VLSISP 2002»
13 years 7 months ago
Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
Bogdan Gabrys
ICIAP
2005
ACM
14 years 7 months ago
A New Efficient Method for Producing Global Affine Invariants
This paper introduces a new efficient way for computing affine invariant features from gray-scale images. The method is based on a novel image transform which produces infinitely m...
Esa Rahtu, Janne Heikkilä, Mikko Salo