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Image understanding using sparse representations / (Record no. 562067)

000 -LEADER
fixed length control field 06339nam a2200805 i 4500
001 - CONTROL NUMBER
control field 6828191
003 - CONTROL NUMBER IDENTIFIER
control field IEEE
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200413152914.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m eo d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cn |||m|||a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140520s2014 caua foab 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781627053600
Qualifying information ebook
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781627053594
Qualifying information paperback
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.2200/S00563ED1V01Y201401IVM015
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number (CaBNVSL)swl00403380
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)880357632
040 ## - CATALOGING SOURCE
Original cataloging agency CaBNVSL
Language of cataloging eng
Description conventions rda
Transcribing agency CaBNVSL
Modifying agency CaBNVSL
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1637.5
Item number .T455 2014
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.6
Edition number 23
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR)
Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) MoCl
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Thiagarajan, Jayaraman Jayaraman.,
Relator term author.
245 10 - TITLE STATEMENT
Title Image understanding using sparse representations /
Statement of responsibility, etc. Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Pavan Turaga, Andreas Spanias.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) :
Name of producer, publisher, distributor, manufacturer Morgan & Claypool,
Date of production, publication, distribution, manufacture, or copyright notice 2014.
300 ## - PHYSICAL DESCRIPTION
Extent 1 PDF (xi, 106 pages) :
Other physical details illustrations.
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term electronic
Source isbdmedia
338 ## - CARRIER TYPE
Carrier type term online resource
Source rdacarrier
490 1# - SERIES STATEMENT
Series statement Synthesis lectures on image, video, and multimedia processing,
International Standard Serial Number 1559-8144 ;
Volume/sequential designation # 15
538 ## - SYSTEM DETAILS NOTE
System details note Mode of access: World Wide Web.
538 ## - SYSTEM DETAILS NOTE
System details note System requirements: Adobe Acrobat Reader.
500 ## - GENERAL NOTE
General note Part of: Synthesis digital library of engineering and computer science.
500 ## - GENERAL NOTE
General note Series from website.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references (pages 91-104).
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction -- 1.1 Modeling natural images -- 1.2 Natural image statistics -- 1.3 Sparseness in biological vision -- 1.4 The generative model for sparse coding -- 1.5 Sparse models for image reconstruction -- 1.5.1 Dictionary design -- 1.5.2 Example applications -- 1.6 Sparse models for recognition -- 1.6.1 Discriminative dictionaries -- 1.6.2 Bag of words and its generalizations -- 1.6.3 Dictionary design with graph embedding constraints -- 1.6.4 Kernel sparse methods --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 2. Sparse representations -- 2.1 The sparsity regularization -- 2.1.1 Other sparsity regularizations -- 2.1.2 Non-negative sparse representations -- 2.2 Geometrical interpretation -- 2.3 Uniqueness of l0 and its equivalence to the l1 solution -- 2.3.1 Phase transitions -- 2.4 Numerical methods for sparse coding -- 2.4.1 Optimality conditions -- 2.4.2 Basis pursuit -- 2.4.3 Greedy pursuit methods -- 2.4.4 Feature-sign search -- 2.4.5 Iterated shrinkage methods --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3. Dictionary learning: theory and algorithms -- 3.1 Dictionary learning and clustering -- 3.1.1 Clustering procedures -- 3.1.2 Probabilistic formulation -- 3.2 Learning algorithms -- 3.2.1 Method of optimal directions -- 3.2.2 K-SVD -- 3.2.3 Multilevel dictionaries -- 3.2.4 Online dictionary learning -- 3.2.5 Learning structured sparse models -- 3.2.6 Sparse coding using examples -- 3.3 Stability and generalizability of learned dictionaries -- 3.3.1 Empirical risk minimization -- 3.3.2 An example case: multilevel dictionary learning --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 4. Compressed sensing -- 4.1 Measurement matrix design -- 4.1.1 The restricted isometry property -- 4.1.2 Geometric interpretation -- 4.1.3 Optimized measurements -- 4.2 Compressive sensing of natural images -- 4.3 Video compressive sensing -- 4.3.1 Frame-by-frame compressive recovery -- 4.3.2 Model-based video compressive sensing -- 4.3.3 Direct feature extraction from compressed videos --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 5. Sparse models in recognition -- 5.1 A simple classification setup -- 5.2 Discriminative dictionary learning -- 5.3 Sparse-coding-based subspace identification -- 5.4 Using unlabeled data in supervised learning -- 5.5 Generalizing spatial pyramids -- 5.5.1 Supervised dictionary optimization -- 5.6 Locality in sparse models -- 5.6.1 Local sparse coding -- 5.6.2 Dictionary design -- 5.7 Incorporating graph embedding constraints -- 5.7.1 Laplacian sparse coding -- 5.7.2 Local discriminant sparse coding -- 5.8 Kernel methods in sparse coding -- 5.8.1 Kernel sparse representations -- 5.8.2 Kernel dictionaries in representation and discrimination -- 5.8.3 Combining diverse features -- 5.8.4 Application: tumor identification --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note Bibliography -- Authors' biographies.
506 1# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Abstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0# - CITATION/REFERENCES NOTE
Name of source Compendex
510 0# - CITATION/REFERENCES NOTE
Name of source INSPEC
510 0# - CITATION/REFERENCES NOTE
Name of source Google scholar
510 0# - CITATION/REFERENCES NOTE
Name of source Google book search
520 3# - SUMMARY, ETC.
Summary, etc. Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blind source separation, super-resolution, and classification.
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Also available in print.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Title from PDF title page (viewed on May 20, 2014).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Image processing
General subdivision Digital techniques
-- Mathematics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Sparse matrices.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer vision.
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term sparse representations
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term natural images
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term image reconstruction
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term image recovery
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term image classification
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term dictionary learning
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term clustering
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term compressed sensing
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term kernel methods
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term graph embedding
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ramamurthy, Karthikeyan Natesan.,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Turaga, Pavan.,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Spanias, Andreas.,
Relator term author.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
International Standard Book Number 9781627053594
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Synthesis digital library of engineering and computer science.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Synthesis lectures on image, video, and multimedia processing ;
Volume/sequential designation # 15.
International Standard Serial Number 1559-8144
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified Abstract with links to resource
Uniform Resource Identifier http://ieeexplore.ieee.org/servlet/opac?bknumber=6828191
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Abstract with links to full text
Uniform Resource Identifier http://dx.doi.org/10.2200/S00563ED1V01Y201401IVM015
Holdings
Withdrawn status Lost status Damaged status Not for loan Permanent Location Current Location Date acquired Barcode Date last seen Price effective from Koha item type
        PK Kelkar Library, IIT Kanpur PK Kelkar Library, IIT Kanpur 2020-04-13 EBKE567 2020-04-13 2020-04-13 E books

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