Machine learning and statistical approaches to image retrieval /

In the early 1990s, the establishment of the Internet brought forth a revolutionary viewpoint of information storage, distribution, and processing: the World Wide Web is becoming an enormous and expanding distributed digital library. Along with the development of the Web, image indexing and retrieva...

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Bibliographic Details
Main Author: Chen, Yixin, 1972-
Corporate Author: SpringerLink (Online service)
Other Authors: Li, Jia, 1974-, Wang, James Z., 1972-
Format: eBook
Language:English
Published: Boston ; London : Kluwer Academic Publishers, [2004]
Series:Kluwer international series on information retrieval ; 14.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:In the early 1990s, the establishment of the Internet brought forth a revolutionary viewpoint of information storage, distribution, and processing: the World Wide Web is becoming an enormous and expanding distributed digital library. Along with the development of the Web, image indexing and retrieval have grown into research areas sharing a vision of intelligent agents. Far beyond Web searching, image indexing and retrieval can potentially be applied to many other areas, including biomedicine, space science, biometric identification, digital libraries, the military, education, commerce, culture and entertainment. Machine Learning and Statistical Modeling Approaches to Image Retrieval describes several approaches of integrating machine learning and statistical modeling into an image retrieval and indexing system that demonstrates promising results. The topics of this book reflect authors' experiences of machine learning and statistical modeling based image indexing and retrieval. This book contains detailed references for further reading and research in this field as well.
Item Description:Electronic resource.
Physical Description:1 online resource (xv, 182 pages) : illustrations
Bibliography:Includes bibliographical references and index.
ISBN:1402080352 (electronic bk.)
9781402080357 (electronic bk.)