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» Combinations of Weak Classifiers
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ECCV
2008
Springer
14 years 12 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof
ICIP
2003
IEEE
14 years 11 months ago
Classification of textures seen from different distances and under varying illumination direction
Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations ...
Xavier Lladó, Joan Martí, Maria Petr...
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
14 years 10 months ago
A parallel learning algorithm for text classification
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...
Canasai Kruengkrai, Chuleerat Jaruskulchai
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
14 years 10 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
CLEF
2010
Springer
13 years 11 months ago
ZOT! to Wikipedia Vandalism - Lab Report for PAN at CLEF 2010
Abstract This vandalism detector uses features primarily derived from a wordpreserving differencing of the text for each Wikipedia article from before and after the edit, along wit...
James White, Rebecca Maessen