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IPMI
2007
Springer
16 years 4 months ago
Localized Components Analysis
We introduce Localized Components Analysis (LoCA) for describing surface shape variation in an ensemble of biomedical objects using a linear subspace of spatially localized shape c...
Dan A. Alcantara, Owen T. Carmichael, Eric Delson,...
206
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ICML
2004
IEEE
16 years 4 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
DATE
2008
IEEE
170views Hardware» more  DATE 2008»
15 years 10 months ago
ETBR: Extended Truncated Balanced Realization Method for On-Chip Power Grid Network Analysis
In this paper, we present a novel simulation approach for power grid network analysis. The new approach, called ETBR for extended truncated balanced realization, is based on model...
Duo Li, Sheldon X.-D. Tan, Bruce McGaughy
143
Voted
WACV
2008
IEEE
15 years 10 months ago
Object Categorization Based on Kernel Principal Component Analysis of Visual Words
In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological in...
Kazuhiro Hotta
105
Voted
ICIP
2007
IEEE
15 years 10 months ago
A Novel Kernel Discriminant Analysis for Face Verification
In this paper a novel non-linear subspace method for face verification is proposed. The problem of face verification is considered as a two-class problem (genuine versus imposto...
Georgios Goudelis, Stefanos Zafeiriou, Anastasios ...