Denoising by semi-supervised kernel PCA preimaging-Reference-Cited by-同舟云学术

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Denoising by semi-supervised kernel PCA preimaging

Published:2014-11 Issue: Volume:49 Page:114-120
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Hansen Toke Jansen,Abrahamsen Trine Julie,Hansen Lars Kai

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference15 articles.

1. Regularized pre-image estimation for kernel PCA de-noising;Abrahamsen;J. Signal Process. Syst.,2011

2. Learning to find pre-images;Bakir,2004

3. Learning to find graph pre-images;Bakir,2004

4. Semi-Supervised Learning;Chapelle,2006

5. S. Dambreville, Y. Rathi, A. Tannenbaum, Statistical shape analysis using kernel PCA, in: IS&T/SPIE Symposium on Electrical Imaging, 2006.

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2. Efficient PCA denoising of spatially correlated redundant MRI data;Imaging Neuroscience;2023-12

3. Deflated manifold embedding PCA framework via multiple instance factorings;Multimedia Tools and Applications;2020-09-24

4. Projection-free kernel principal component analysis for denoising;Neurocomputing;2019-09

5. An improved kernel principal component analysis based on sparse representation for face recognition;KSII Transactions on Internet and Information Systems;2016-06-30

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