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PR
2006
115views more  PR 2006»
13 years 7 months ago
Diagonal principal component analysis for face recognition
In this paper, a novel subspace method called diagonal principal component analysis (DiaPCA) is proposed for face recognition. In contrast to standard PCA, DiaPCA directly seeks t...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
DATASCIENCE
2002
84views more  DATASCIENCE 2002»
13 years 7 months ago
The application of Principal Component Analysis to materials science data
The relationship between apparently disparate sets of data is a critical component of interpreting materials' behavior, especially in terms of assessing the impact of the mic...
Changwon Suh, Arun Rajagopalan, Xiang Li, Krishna ...
COMPLIFE
2006
Springer
13 years 11 months ago
Set-Oriented Dimension Reduction: Localizing Principal Component Analysis Via Hidden Markov Models
We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov model...
Illia Horenko, Johannes Schmidt-Ehrenberg, Christo...
JMLR
2012
11 years 10 months ago
Sparse Higher-Order Principal Components Analysis
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
Genevera Allen
ICIP
2008
IEEE
14 years 9 months ago
Principal Component Analysis of spectral coefficients for mesh watermarking
This paper proposes a new robust 3-D object blind watermarking method using constraints in the spectral domain. Mesh watermarking in spectral domain has the property of spreading ...
Ming Luo, Adrian G. Bors