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  1. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
  2. 2003 Conference on Computer Vision and Pattern Recognition Workshop
  3. Volume 6 - 2003
  4. Kernel Pooled Local Subspaces for Classification
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2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops
2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
CVPR 2011 WORKSHOPS
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops
2004 Conference on Computer Vision and Pattern Recognition Workshop
2003 Conference on Computer Vision and Pattern Recognition Workshop
Volume 9 - 2003
Volume 8 - 2003
Volume 7 - 2003
Volume 6 - 2003
Coevolutionary Computation for Synthesis of Recognition Systems
MDL-based Genetic Programming for Object Detection
Learning Visual Feature Detectors for Obstacle Avoidance using Genetic Programming
Iterative Relief
Kernel Pooled Local Subspaces for Classification
Robust Fusion of Uncertain Information
An Integrated Learning Framework for Recognition Based on Images
Carving Prior Manifolds Using Inequalities
Two Sequential Stages Classifier for Multispectral Data
Texture Structure Classification and Depth Estimation using Multi-Scale Local Autocorrelation Features
Volume 5 - 2003
Volume 4 - 2003
Volume 3 - 2003
Volume 2 - 2003
Volume 1 - 2003
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition

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Kernel Pooled Local Subspaces for Classification

Content Provider IEEE Xplore Digital Library
Author Zhang, Peng Peng, Jing Domeniconi, Carlotta
Copyright Year 2003
Description Author affiliation: George Mason University (Domeniconi, Carlotta) || Tulane University (Zhang, Peng; Peng, Jing)
Abstract We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and compare it against several competing techniques: Principal Component Analysis (PCA), Kernel PCA (KPCA), and linear local pooling in classification problems. We evaluate the classification performance of the nearest-neighbor rule with each subspace representation. The experimental results demonstrate the effectiveness and performance superiority of the kernel pooled subspace method over competing methods such as PCA and KPCA in some classification problems.
Starting Page 63
Ending Page 63
File Size 171455
Page Count 1
File Format PDF
ISBN 0769519008
ISSN 10636919
DOI 10.1109/CVPRW.2003.10060
Language English
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date 2003-06-16
Publisher Place USA
Access Restriction Subscribed
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword Training Computer vision Conferences Glass Eigenvalues and eigenfunctions Kernel Principal component analysis
Content Type Text
Resource Type Article
Subject Computer Vision and Pattern Recognition Software
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