Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Cognitive Technologies (COGTECH)
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Table of contents (11 chapters)
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Front Matter
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Introduction to Learning Principles for Multimedia Data
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Front Matter
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Multimedia Applications
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Front Matter
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Back Matter
Keywords
About this book
Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations – the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply.
This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.
This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
Editors and Affiliations
Bibliographic Information
Book Title: Machine Learning Techniques for Multimedia
Book Subtitle: Case Studies on Organization and Retrieval
Editors: Matthieu Cord, Pádraig Cunningham
Series Title: Cognitive Technologies
DOI: https://doi.org/10.1007/978-3-540-75171-7
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-75170-0Published: 26 February 2008
Softcover ISBN: 978-3-642-44362-6Published: 23 September 2014
eBook ISBN: 978-3-540-75171-7Published: 07 February 2008
Series ISSN: 1611-2482
Series E-ISSN: 2197-6635
Edition Number: 1
Number of Pages: XVI, 289
Topics: Artificial Intelligence, Information Storage and Retrieval, User Interfaces and Human Computer Interaction, Data Mining and Knowledge Discovery, Natural Language Processing (NLP), Computer Imaging, Vision, Pattern Recognition and Graphics