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Herausgeber: 
  • Matthieu Cord
  • Pádraig Cunningham
  • Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Februar 2008  
    Genre:  EDV / Informatik 
     
    Bildverarbeitung / Biometrics / Biometrie / Classification / clustering / Cognition / Data Mining / Data Warehousing
    ISBN:  9783540751700 
    EAN-Code: 
    9783540751700 
    Verlag:  Springer 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Cognitive Technologies  
    Dimensionen:  H 241 mm / B 160 mm / D 22 mm 
    Gewicht:  629 gr 
    Seiten:  308 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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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