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ECCV
2004
Springer
14 years 10 months ago
Dimensionality Reduction by Canonical Contextual Correlation Projections
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
Marco Loog, Bram van Ginneken, Robert P. W. Duin
IGARSS
2009
13 years 6 months ago
Classification Performance of Random-projection-based Dimensionality Reduction of Hyperspectral Imagery
High-dimensional data such as hyperspectral imagery is traditionally acquired in full dimensionality before being reduced in dimension prior to processing. Conventional dimensiona...
James E. Fowler, Qian Du, Wei Zhu, Nicolas H. Youn...
PCM
2004
Springer
99views Multimedia» more  PCM 2004»
14 years 2 months ago
Indexing Issues in Supporting Similarity Searching
Indexing issues that arise in the support of similarity searching are presented. This includes a discussion of the curse of dimensionality, as well as multidimensional indexing, di...
Hanan Samet
JCP
2007
149views more  JCP 2007»
13 years 8 months ago
Partitional Clustering Techniques for Multi-Spectral Image Segmentation
Abstract— Analyzing unknown data sets such as multispectral images often requires unsupervised techniques. Data clustering is a well known and widely used approach in such cases....
Danielle Nuzillard, Cosmin Lazar
GECCO
2010
Springer
175views Optimization» more  GECCO 2010»
14 years 1 months ago
Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noiseless testbed
We implement a weighted negative update of the covariance matrix in the CMA-ES—weighted active CMA-ES or, in short, aCMA-ES. We benchmark the IPOP-aCMA-ES and compare the perfor...
Nikolaus Hansen, Raymond Ros