MACHINE LEARNING TECHNIQUES FOR MULTIMEDIA: CASE STUDIES ON ORGANIZATION AND RETRIEVAL. Cet article n’est pas disponible.
Langue : anglais
Edité par SPRINGER, 2008
- Livre relié
- Occasion
Vendeur : UK BOOKS STORE, London, London, Royaume-UniUK BOOKS STORE
Vendeur AbeBooks depuis 11 mars 2024
Etat: Occasion
EUR 247,71
A propos de cet article
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N° de réf. du vendeur Adhy 9783540751700
- Titre
- MACHINE LEARNING TECHNIQUES FOR MULTIMEDIA: CASE STUDIES ON ORGANIZATION AND RETRIEVAL
- Auteur
- CORD MATTHIEU ET.AL
- Éditeur
- SPRINGER
- Année de publication
- 2008
- État de l'article
- New Books
- Reliure
- Hardcover
- Langue
- anglais
- ISBN à 10 chiffres
- 354075170X
- ISBN à 13 chiffres
- 9783540751700
- Édition
- Edition internationale
- Série
- Livre 9 sur 43: Cognitive Technologies
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. Arising from the EU MUSCLE network, this multidisciplinary book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain.
« Synopsis » peut appartenir à une autre édition de cet ouvrage.
À propos de la quatrième de couverture
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.
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