429 search results - page 8 / 86 » Unsupervised feature selection for principal components anal... |
CVPR
2006
IEEE
14 years 9 months ago
2006
IEEE
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...
IGARSS
2009
13 years 5 months ago
2009
Kernel Principal Component Analysis (KPCA) is investigated for feature extraction from hyperspectral remotesensing data. Features extracted using KPCA are used to construct the Ex...
ICDM
2006
IEEE
14 years 1 months ago
2006
IEEE
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
TIT
2002
13 years 7 months ago
2002
Principal curves, like principal components, are a tool used in multivariate analysis for ends like feature extraction. Defined in their original form, principal curves need not ex...
HAPTICS
2007
IEEE
14 years 1 months ago
2007
IEEE
A method based on Principal Component Analysis of the fingernail coloration pattern is presented to infer fingertip force direction during planar contact. Images from 7 subjects...