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» HITS is Principal Components Analysis
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77
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ICIP
2002
IEEE
16 years 2 months ago
Face recognition using mixtures of principal components
We introduce an efficient statistical modeling technique called Mixture of Principal Components (MPC). This model is a linear extension to the traditional Principal Component Anal...
Deepak S. Turaga, Tsuhan Chen
113
Voted
ISBI
2007
IEEE
15 years 6 months ago
Statistical Shape Analysis via Principal Factor Analysis
Statistical shape analysis techniques commonly employed in the medical imaging community, such as Active Shape Models or Active Appearance Models, rely on Principal Component Anal...
Mauricio Reyes, Marius George Linguraru, Kostas Ma...
BMCBI
2006
183views more  BMCBI 2006»
15 years 14 days ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
104
Voted
ICRA
1998
IEEE
148views Robotics» more  ICRA 1998»
15 years 4 months ago
Position Estimation Using Principal Components of Range Data
1 sensors is to construct a structural description from sensor data and to match this description to a previously acquired model [Crowley 85]. An alternative is to project individu...
James L. Crowley, Frank Wallner, Bernt Schiele
92
Voted
CVPR
2006
IEEE
16 years 2 months ago
Selecting Principal Components in a Two-Stage LDA Algorithm
Linear Discriminant Analysis (LDA) is a well-known and important tool in pattern recognition with potential applications in many areas of research. The most famous and used formul...
Aleix M. Martínez, Manli Zhu