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ECML
2001
Springer
14 years 1 months ago
Learning of Variability for Invariant Statistical Pattern Recognition
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...
Daniel Keysers, Wolfgang Macherey, Jörg Dahme...
TSMC
2008
182views more  TSMC 2008»
13 years 8 months ago
Incremental Linear Discriminant Analysis for Face Recognition
Abstract--Dimensionality reduction methods have been successfully employed for face recognition. Among the various dimensionality reduction algorithms, linear (Fisher) discriminant...
Haitao Zhao, Pong Chi Yuen
KDD
2007
ACM
137views Data Mining» more  KDD 2007»
14 years 9 months ago
Characterising the difference
Characterising the differences between two databases is an often occurring problem in Data Mining. Detection of change over time is a prime example, comparing databases from two b...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
ISMB
2000
13 years 10 months ago
Pattern Recognition of Genomic Features with Microarrays: Site Typing of Mycobacterium Tuberculosis Strains
Mycobacterium tuberculosis (M. tb.) strains differ in the number and locations of a transposon-like insertion sequence known as IS6110. Accurate detection of this sequence can be ...
Soumya Raychaudhuri, Joshua M. Stuart, Xuemin Liu,...
CVPR
2005
IEEE
14 years 11 months ago
Object Class Recognition Using Multiple Layer Boosting with Heterogeneous Features
We combine local texture features (PCA-SIFT), global features (shape context), and spatial features within a single multi-layer AdaBoost model of object class recognition. The fir...
Wei Zhang 0002, Bing Yu, Gregory J. Zelinsky, Dimi...