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» Position Estimation Using Principal Components of Range Data
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TNN
1998
121views more  TNN 1998»
13 years 5 months ago
Detection of mines and minelike targets using principal component and neural-network methods
— This paper introduces a new system for real-time detection and classification of arbitrarily scattered surface-laid mines from multispectral imagery data of a minefield. The ...
Xi Miao, Mahmood R. Azimi-Sadjadi, Bin Tan, A. C. ...
CSDA
2008
158views more  CSDA 2008»
13 years 5 months ago
Outlier identification in high dimensions
A computationally fast procedure for identifying outliers is presented, that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal c...
Peter Filzmoser, Ricardo A. Maronna, Mark Werner
ICPR
2006
IEEE
14 years 6 months ago
Multilinear Principal Component Analysis of Tensor Objects for Recognition
In this paper, a multilinear formulation of the popular Principal Component Analysis (PCA) is proposed, named as multilinear PCA (MPCA), where the input can be not only vectors, b...
Anastasios N. Venetsanopoulos, Haiping Lu, Konstan...
CORR
2010
Springer
130views Education» more  CORR 2010»
13 years 5 months ago
Stable Principal Component Pursuit
In this paper, we study the problem of recovering a low-rank matrix (the principal components) from a highdimensional data matrix despite both small entry-wise noise and gross spar...
Zihan Zhou, Xiaodong Li, John Wright, Emmanuel J. ...
ADBIS
2003
Springer
108views Database» more  ADBIS 2003»
13 years 10 months ago
Dynamic Integration of Classifiers in the Space of Principal Components
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
Alexey Tsymbal, Mykola Pechenizkiy, Seppo Puuronen...