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ICCV
2007
IEEE
14 years 9 months ago
High-Dimensional Feature Matching: Employing the Concept of Meaningful Nearest Neighbors
Matching of high-dimensional features using nearest neighbors search is an important part of image matching methods which are based on local invariant features. In this work we hi...
Dusan Omercevic, Ondrej Drbohlav, Ales Leonardis
TMI
2011
127views more  TMI 2011»
13 years 2 months ago
Reconstruction of Large, Irregularly Sampled Multidimensional Images. A Tensor-Based Approach
Abstract—Many practical applications require the reconstruction of images from irregularly sampled data. The spline formalism offers an attractive framework for solving this prob...
Oleksii Vyacheslav Morozov, Michael Unser, Patrick...
ICIAP
2005
ACM
14 years 7 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
JMLR
2010
367views more  JMLR 2010»
13 years 2 months ago
Locally Linear Denoising on Image Manifolds
We study the problem of image denoising where images are assumed to be samples from low dimensional (sub)manifolds. We propose the algorithm of locally linear denoising. The algor...
Dian Gong, Fei Sha, Gérard G. Medioni
CDC
2009
IEEE
185views Control Systems» more  CDC 2009»
14 years 8 days ago
Discrete Empirical Interpolation for nonlinear model reduction
A dimension reduction method called Discrete Empirical Interpolation (DEIM) is proposed and shown to dramatically reduce the computational complexity of the popular Proper Orthogo...
Saifon Chaturantabut, Danny C. Sorensen