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Subspace Methods for Pattern Recognition in Intelligent Environment

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Cover of 'Subspace Methods for Pattern Recognition in Intelligent Environment'

Table of Contents

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    Book Overview
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    Chapter 1 Active Shape Model and Its Application to Face Alignment
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    Chapter 2 Condition Relaxation in Conditional Statistical Shape Models
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    Chapter 3 Independent Component Analysis and Its Application to Classification of High-resolution Remote Sensing Images
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    Chapter 4 Subspace Construction from Artificially Generated Images for Traffic Sign Recognition
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    Chapter 5 Local Structure Preserving Based Subspace Analysis Methods and Applications
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    Chapter 6 Sparse Representation for Image Super-Resolution
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    Chapter 7 Sampling and Recovery of Continuously-Defined Sparse Signals and Its Applications
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    Chapter 8 Tensor-Based Subspace Learning for Multi-pose Face Synthesis
Attention for Chapter 7: Sampling and Recovery of Continuously-Defined Sparse Signals and Its Applications
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Chapter title
Sampling and Recovery of Continuously-Defined Sparse Signals and Its Applications
Chapter number 7
Book title
Subspace Methods for Pattern Recognition in Intelligent Environment
Published by
Springer, Berlin, Heidelberg, January 2014
DOI 10.1007/978-3-642-54851-2_7
Book ISBNs
978-3-64-254850-5, 978-3-64-254851-2
Authors

Akira Hirabayashi, Hirabayashi, Akira

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 100%
Readers by discipline Count As %
Engineering 1 100%

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