E-Book, Englisch, Band 30, 277 Seiten, eBook
E-Book, Englisch, Band 30, 277 Seiten, eBook
Reihe: Multimedia Systems and Applications
ISBN: 978-0-387-69942-4
Verlag: Springer US
Format: PDF
Kopierschutz: Wasserzeichen (»Systemvoraussetzungen)
introduces machine learning techniques that are particularly powerful and effective for modeling spatial, temporal structures of multimedia data and for accomplishing common tasks of multimedia content analysis. This book systematically covers these techniques in an intuitive fashion and demonstrates their applications through case studies. This volume uses a large number of figures to illustrate and visualize complex concepts, and provides insights into the characteristics of many algorithms through examinations of their loss functions and straightforward comparisons.
Machine Learning for Multimedia Content Analysis
is designed for an academic and professional audience. Researchers will find this book an invaluable tool for applying machine learning techniques to multimedia content analysis. This volume is also suitable for practitioners in industry.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Unsupervised Learning.- Dimension Reduction.- Data Clustering Techniques.- Generative Graphical Models.- of Graphical Models.- Markov Chains and Monte Carlo Simulation.- Markov Random Fields and Gibbs Sampling.- Hidden Markov Models.- Inference and Learning for General Graphical Models.- Discriminative Graphical Models.- Maximum Entropy Model and Conditional Random Field.- Max-Margin Classifications.