Machine Learning for Multimedia Content Analysis

Gong, Yihong; Xu, Wei

ISBN 10: 0387699384 / ISBN 13: 9780387699387

Edité par Springer-Verlag New York Inc., 2007

A propos de cet article

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. Series: Multimedia Systems and Applications. Num Pages: 293 pages, 20 black & white illustrations, 10 black & white tables, biography. BIC Classification: UG; UYQM. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 17. Weight in Grams: 592. . 2007. Hardback. . . . . Books ship from the US and Ireland.

N° de réf. du vendeur V9780387699387

Détails bibliographiques

• Titre: Machine Learning for Multimedia Content Analysis
• Éditeur: Springer-Verlag New York Inc.
• Date de parution: 2007
• Langue: anglais
• ISBN à 10 chiffres: 0387699384
• ISBN à 13 chiffres: 9780387699387
• Reliure: Couverture rigide
• État de l'article: New

A propos de ce titre

Synopsis

Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. 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).

Présentation de l'éditeur

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.