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PR
2006
115views more  PR 2006»
15 years 1 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»
15 years 1 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
15 years 5 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
13 years 4 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
16 years 3 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