Call for Papers: Machine learning for big multimedia analytics 
With the rapid development of digital multimedia sensing and communication technology, multimedia data has been acquired, processed and shared explosively, becoming an indispensable part of today's big data. Such big multimedia data has inherent opportunities and challenges of managing, searching and understanding, which requires to understand how humans perceive cognitive concepts. With the recent advances in machine learning techniques, we are now able to boost the intelligence of multimedia analysis significantly. Machine learning for big multimedia analytics is becoming an emerging research area in the field of multimedia and computer vision. This has attracted massive research efforts devoted to address challenges in the area of multimedia computing. Machine learning technology has been widely used in recent years to address complex and challenging real-world vision processing problems, including visual surveillance, smart cities, and social multimedia network. The special issue aims to provide a collection of high quality research articles that address the broad challenges in both theoretical and application aspects of machine learning for big multimedia analytics.
Topics of interest include, but are not limited to:
- Fundamental machine learning theory and technologies
- Machine learning for multimedia processing, restoration and enhancement
- Machine learning for multimedia analytics, object detection and tracking, event recognition, behavior understanding
- Machine learning for multimedia compression, coding and transmission
- Applications of machine learning for multimedia analytics, such as healthcare, surveillance, social multimedia network, and other applications
Dr. Tian Jing (Lead Guest Editor), National University of Singapore, Singapore, Email: email@example.com
Dr. Xin Xu, Wuhan University of Science and Technology, Wuhan, China, Email: firstname.lastname@example.org
Submission of manuscripts: extended to June 30, 2020
First revision notification: September 15, 2020
Submission of revised papers: October 15, 2020
Final acceptance/rejection notice: November 30, 2020
Authors should prepare their manuscript according to the Submission Guidelines/Instructions for Authors available from the Multimedia Tools and Applications website (https://www.springer.com/11042).
Authors should submit through the online submission site at https://www.editorialmanager.com/mtap/default.aspx and select “SI 1162 - Machine learning for big multimedia analytics” when they reach the “Article Type” step in the submission process. Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least three independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process.