• DocumentCode
    3091713
  • Title

    Multimedia Analysis with Deep Learning

  • Author

    Qingbo Wu ; Hua Zhang ; Si Liu ; Xiaochun Cao

  • Author_Institution
    State Key Lab. of Inf. Security, China
  • fYear
    2015
  • fDate
    20-22 April 2015
  • Firstpage
    20
  • Lastpage
    23
  • Abstract
    Recently, deep learning method has been attracting more and more researchers due to its great success in various computer vision tasks. Particularly, some researchers focus on the study of multimedia analysis by deep learning method, and the research tasks mainly include the following six aspects: classification, retrieval, segmentation, tracking, detection and recommendation. As far as we know, there is not any literature conducting on survey of these studies, and it is of great significance for the community to review this subject. In this paper, we discuss the application of deep learning method in the six multimedia analysis tasks, and also point out the future directions of deep learning in multimedia analysis.
  • Keywords
    computer vision; image classification; image retrieval; image segmentation; learning (artificial intelligence); multimedia systems; object detection; object tracking; computer vision; deep learning method; image classification; image detection; image recommendation; image retrieval; image segmentation; image tracking; multimedia analysis; Brain models; Feature extraction; Learning systems; Multimedia communication; Neural networks; Tracking; classification; deep learning; detection; multimedia analysis; recommendation; retrieval; segmentation; tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Big Data (BigMM), 2015 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-8687-3
  • Type

    conf

  • DOI
    10.1109/BigMM.2015.27
  • Filename
    7153770