NDLI: Discriminant Isomap projection

Content Provider	IEEE Xplore Digital Library
Author	Ya-Li Zheng Tai-Ping Zhang Bin Fang Yuan-Yan Tang
Copyright Year	2009
Description	Author affiliation: School of Computer Science, Chongqing University, 40030, China (Ya-Li Zheng; Tai-Ping Zhang; Bin Fang; Yuan-Yan Tang)
Abstract	In this paper we proposed a novel supervised dimensionality reduction method, named Discriminant Isometric projection. The aim is to compact the data points from the same cluster on high-dimension manifold to make them closer in the low-dimension space, and to make the ones from the different cluster further, which is beneficial to preserve the homogeneous characteristics for classification. We compared our method with other three methods for dimensionality reduction over the ORL face dataset and experiments show that Discriminant Isometric projection produces stable performance and good precision.
Starting Page	144
Ending Page	147
File Size	235492
Page Count	4
File Format	PDF
ISBN	9781424437283
DOI	10.1109/ICWAPR.2009.5207418
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dimensionality reduction Embedded computing Face recognition Wavelet analysis Projection Pattern recognition Supervised Computer science Classification Eigenvalues and eigenfunctions Linear discriminant analysis Pattern analysis Kernel Principal component analysis
Content Type	Text
Resource Type	Article

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