Machine Learning for Multimedia Content Analysis
(Sprache: Englisch)
This volume introduces machine learning techniques that are particularly effective for modeling multimedia data and common tasks of multimedia content analysis. It demonstrates the application of key machine learning techniques through case studies.
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Produktinformationen zu „Machine Learning for Multimedia Content Analysis “
This volume introduces machine learning techniques that are particularly effective for modeling multimedia data and common tasks of multimedia content analysis. It demonstrates the application of key machine learning techniques through case studies.
Klappentext zu „Machine Learning for Multimedia Content Analysis “
This volume introduces machine learning techniques that are particularly powerful and effective for modeling multimedia data and common tasks of multimedia content analysis. It systematically covers key machine learning techniques in an intuitive fashion and demonstrates their applications through case studies. Coverage includes examples of unsupervised learning, generative models and discriminative models. In addition, the book examines Maximum Margin Markov (M3) networks, which strive to combine the advantages of both the graphical models and Support Vector Machines (SVM).
Inhaltsverzeichnis zu „Machine Learning for Multimedia Content Analysis “
- Preface- Introduction
- Unsupervised Learning
- Clustering Techniques
- Principal Conmponent Analysis
- Generative Graphical Models
- Markov Models
- Hidden Markov Models
- General Graphical Models
- Discriminative Graphical Models
- Conditional Random Fields
- Neural Networks
- Maximum Margin Markov Networks
- Index
Bibliographische Angaben
- Autoren: Yihong Gong , Wei Xu
- 2007, 2007, 277 Seiten, 20 Abbildungen, Masse: 16 x 24,1 cm, Gebunden, Englisch
- Verlag: Springer
- ISBN-10: 0387699384
- ISBN-13: 9780387699387
- Erscheinungsdatum: 01.10.2007
Sprache:
Englisch
Rezension zu „Machine Learning for Multimedia Content Analysis “
From the reviews:"The objectives of this book are to bring together powerful machine learning techniques that are suitable for modeling multimedia data, and to showcase their application to common multimedia content analysis tasks. The book is designed for students and researchers who want to apply machine learning techniques to multimedia content analysis. ... Motivated researchers working in this field can certainly benefit by reading about the methods and case studies described here. It could also serve as a good reference ... ." (Rao Vemuri, Computing Reviews, Vol. 50 (1), January, 2009)
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