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» Outlier Removal Using Duality
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AIR
2004
131views more  AIR 2004»
13 years 4 months ago
A Survey of Outlier Detection Methodologies
Abstract. Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes ...
Victoria J. Hodge, Jim Austin
BMCBI
2006
187views more  BMCBI 2006»
13 years 4 months ago
Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
Harvey J. Motulsky, Ronald E. Brown
ICML
2000
IEEE
14 years 5 months ago
Duality and Geometry in SVM Classifiers
We develop an intuitive geometric interpretation of the standard support vector machine (SVM) for classification of both linearly separable and inseparable data and provide a rigo...
Kristin P. Bennett, Erin J. Bredensteiner
IMAGING
2003
13 years 6 months ago
Using Colour to Model Outliers
Computer vision applications are able to model and reconstruct three dimensional scenes from several pictures. In this work, we are interested in the group of algorithm that regis...
David Hasler, Sabine Süsstrunk
ETFA
2008
IEEE
13 years 11 months ago
Two camera system for robot applications; navigation
Current approaches to feature detection and matching in images strive to increase the repeatability of the detector and minimize the degree of outliers in the matching. In this pa...
Jörgen Lidholm, Fredrik Ekstrand, Lars Asplun...