Foundations of Large-Scale Multimedia Information Management and Retrieval - Mathematics of Perception (Paperback, 2011 ed.)

"Foundations of Large-Scale Multimedia Information Management and Retrieval: Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and multimodal fusion. Part II - Scalability Issues presents indexing and distributed methods for scaling up these components for high-dimensional data and Web-scale datasets. The book presents some real-world applications and remarks on future research and development directions. The book is designed for researchers, graduate students, and practitioners in the fields of Computer Vision, Machine Learning, Large-scale Data Mining, Database, and Multimedia Information Retrieval. Dr. Edward Y. Chang was a professor at the Department of Electrical & Computer Engineering, University of California at Santa Barbara, before he joined Google as a research director in 2006. Dr. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Release date:	November 2014
First published:	2011
Authors:	Edward Y. Chang
Dimensions:	235 x 155 x 17mm (L x W x T)
Format:	Paperback
Pages:	291
Edition:	2011 ed.
ISBN-13:	978-3-642-44128-8
Categories:	Books > Computing & IT > Computer software packages > Multimedia Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Mechanical engineering & materials > Mechanical engineering > Engines & power transmission > General
LSN:	3-642-44128-9
Barcode:	9783642441288

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