Machine learning and statistical modeling approaches to image retrieval / Yixin Chen, Jia Li, James...
Machine learning and statistical modeling approaches to image retrieval / Yixin Chen, Jia Li, James...
Machine learning and statistical modeling approaches to image retrieval / Yixin Chen, Jia Li, James Z. Wang.
About this item
Full title
Author / Creator
Publisher
Boston : Kluwer Academic Publishers, c2004.
Call Numbers
N621.367/57
Record Identifier
MMS ID
Language
English
Formats
Physical Description
Physical content
xv, 182 p. : ill. ; 25 cm.
Contents
1. Introduction -- 2. Image retrieval and linguistic indexing -- 3. Machine learning and statistical modeling -- 4. A robust region-based similarity measure -- 5. Cluster-based retrieval by unsupervised learning -- 6. Categorization by learning and reasoning with regions -- 7. Automatic linguistic i...
Publication information
Publisher
Boston : Kluwer Academic Publishers, c2004.
Place of Publication
Massachusetts
Date Published
c2004.
Subjects
More information
Scope and Contents
Summary
"Machine Learning and Statistical Modeling Approaches to Image Retrieval is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and electrical engineering."--BOOK JACKET.
Alternative Titles
Full title
Machine learning and statistical modeling approaches to image retrieval / Yixin Chen, Jia Li, James Z. Wang.
Authors, Artists and Contributors
Author / Creator
Author / Artists
Notes
General note
The Kluwer international series on information retrieval ; 14.
Includes bibliographical references (p. [173]-179) and index.
Contextual Information
Date Copyright
c2004.
Identifiers
Primary Identifiers
Call Numbers
N621.367/57
Record Identifier
74VKwvMwgxMl
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/74VKwvMwgxMl
Other Identifiers
ISBN
1402080352 (e-book)
9781402080340 (alk. paper)
1402080344 (alk. paper)
9781402080357 (e-book)
DDC
621.367
MMS ID
991018288169702626
