CFP for Special Session on

Applications of Machine Learning in Multimedia Content Analysis



Fifth International Conference on Machine Learning and Applications (ICMLA’ 06)


December 14-16, 2005 - Orlando, Florida, USA


    Automatic processing of multimedia contents has become as a key area for machine learning applications. Applying machine learning technique for automatic multimedia content analysis has many benefits: (a) semantic multimedia content understanding; (b) improving the performances of the techniques for multimedia content analysis; (c) supporting more effective solutions for multimedia data organization and indexing; (d) enhancing efficiency and accuracy for multimedia search.

    Multimedia contents have some specific characteristics that place very specific demands for the relevant machine learning techniques, such as high-dimensional issues and semantic gap. Machine learning may play a crucial role on improving the performance of the techniques for multimedia content analysis and retrieval. This special session tries to bring the interaction between two relevant research areas: multimedia content analysis and machine learning.

The interesting topics include: 

The special session will be an integral part of the ICMLA’06 conference. Paper must correspond to the requirements detailed in the instructions to the authors, which are placed to the conference web site. All accepted papers must be presented by one of the authors to be published in the conference proceeding. Selected best papers accepted for the special session will be invited for publication in a Journal.

Please submit your paper in the form of PDF files and conforming to IEEE specifications at the following website:

Instructions for authors:

Authors' guidelines for Word

Authors' guidelines for LaTeX

Authors' guidelines for LyX

IEEE PDF specification


Please do not hesitate to direct your questions to the special session organizers listed below: 

Jianping Fan

University of North Carolina at Charlotte


Xingquan Zhu

University of Vermont


Xiangyang Xue

Fudan University