Technical Demos

IEEE BigMM is a world premier forum of leading researchers in the highly active multimedia big data research, development and applications. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Multimedia big data includes but is not limited to text, image, graphics, audio, video, social, and sensor data that is of large volume and highly valuable in decision making. It covers from everyone experiences to everything happening in the world. As such, multimedia big data is spurring on tremendous amount of research and development of related technologies and applications.

IEEE BigMM 2020 will provide technical demo session that will be held during the conference. Demos are intended as real, practical, and interactive proof of the presenters’ research ideas and scientific or engineering contributions, with the goal of providing multimedia big data researchers and practitioners with the opportunity to discuss working multimedia systems, applications, prototypes, or proof-of-concepts. Such a setting allows conference attendants to view and interact first hand with live evidence of innovative solutions and ideas in the field of multimedia big data and to see cutting edge research in various interdisciplinary fields. Submissions are encouraged in any of the technical areas related to multimedia big data, as described in IEEE BigMM 2020 general call for
papers: 
http://bigmm.midas.iiitd.edu.in/index.php/calls-for-submission/call-for-papers

Once accepted, demonstrators/ presenters will be provided with a table, poster board, power outlet and wireless (shared) Internet. All other equipment needs to be arranged by the presenters. However, if you have special requests such as a larger space, special lighting conditions and so on, we will do our best to arrange them.

Submission Guidelines

The documents should be submitted through the submission
system:https://easychair.org/conferences/?conf=bigmm2020