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E-Book

E-Book, Englisch, 291 Seiten

Chang Foundations of Large-Scale Multimedia Information Management and Retrieval

Mathematics of Perception
1. Auflage 2011
ISBN: 978-3-642-20429-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

Mathematics of Perception

E-Book, Englisch, 291 Seiten

ISBN: 978-3-642-20429-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark



'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.

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. Edward Y. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.

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