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ICASSP
2008
IEEE
15 years 3 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
15 years 1 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
14 years 9 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
15 years 3 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
15 years 11 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