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NOSSDAV 2018 : Network and Operating System Support for Digital Audio and Video


Conference Series : Network and Operating System Support for Digital Audio and Video
When Jun 15, 2018 - Jun 15, 2018
Where Amsterdam, The Netherlands
Submission Deadline Mar 1, 2018
Notification Due Apr 9, 2018
Final Version Due Apr 19, 2018
Categories    multimedia   video   audio   operating systems

Call For Papers

The 28th ACM SIGMM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV 2018) will be co-located with ACM MMSys 2018, which will be held during June 12 - 15, 2018 in Amsterdam, The Netherlands. As usual, the Proceedings of NOSSADAV 2018 will be published by ACM and distributed at the workshop electronically, and will also be included in the ACM Digital Library.

As in previous years, the workshop will continue to focus on both established and emerging research topics, high-risk high-return ideas and proposals, and future research directions in multimedia networking and systems, in a single-track format the encourages active participation and discussions among academic and industry researchers and practitioners. Out-of-the-box ideas are particularly welcome.

The workshop seeks papers in all areas of multimedia networking and systems. Authors are especially encouraged to submit papers with real-world experimental results and real data sets. Topics of interest include, but are not limited to the following.

Applications for social media and networks
Augmented reality (AR) and virtual reality (VR)
Energy-aware and green computing
Media streaming, distribution and storage
Mobile, cloud, and peer-to-peer systems
Multi-core and many-core systems
Health care and quality of life
Multimedia communications
Multimedia data analytics and visualization
Networked games
Networked GPUs, graphics, and virtual environments
Real-time immersive systems
System security
Visual search
Web 2.0 systems and social networks
Wireless networks and embedded systems for multimedia applications
Systems for computer vision applications
Machine learning for multimedia systems

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