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ICASSP
2008
IEEE
14 years 2 months ago
An ICA-based multilinear algebra tools for dimensionality reduction in hyperspectral imagery
Dimensionality reduction (DR) is a major issue to improve the efficiency of the classifiers in Hyperspectral images (HSI). Recently, the independent component analysis (ICA) app...
Nadine Renard, Salah Bourennane
CIARP
2006
Springer
13 years 11 months ago
Automatic Band Selection in Multispectral Images Using Mutual Information-Based Clustering
Feature selection and dimensionality reduction are crucial research fields in pattern recognition. This work presents the application of a novel technique on dimensionality reducti...
Adolfo Martínez Usó, Filiberto Pla, ...
IDA
1998
Springer
13 years 7 months ago
Fast Dimensionality Reduction and Simple PCA
A fast and simple algorithm for approximately calculating the principal components (PCs) of a data set and so reducing its dimensionality is described. This Simple Principal Compo...
Matthew Partridge, Rafael A. Calvo
IBPRIA
2007
Springer
14 years 1 months ago
False Positive Reduction in Breast Mass Detection Using Two-Dimensional PCA
In this paper we present a novel method for reducing false positives in breast mass detection. Our approach is based on using the Two-Dimensional Principal Component Analysis (2DPC...
Arnau Oliver, Xavier Lladó, Joan Mart&iacut...
CVPR
2008
IEEE
14 years 9 months ago
Clustering and dimensionality reduction on Riemannian manifolds
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
Alvina Goh, René Vidal