[Comp-neuro] CFP: Signal Processing Special Issue on Big Data Meets Multimedia Analytics

刘伟锋 liuwfxy at gmail.com
Sun Feb 8 03:23:21 CET 2015


Dear all,

Sorry for  the cross posting of this CFP message.

CFP: Signal Processing Special Issue on Big Data Meets Multimedia Analytics

With the rapid development of computing and sensing technologies, such as
the emergence of social networking websites and wearable devices, many new
research opportunities and challenges for multimedia content analysis have
arisen.

Many big data modeling methods, computing algorithms, and signal processing
technologies have recently been successfully developed and applied to
multimedia content analysis: for example, multi-view learning algorithms
have been proposed for exploring the variety of multimedia content; sparse
and manifold learning have been developed for high dimensional multimedia
data representation; deep learning has produced promising results in large
scale multimedia retrieval; and compressive sensing and new sampling
schemes have been investigated for big data analytics.

Motivated by the inclination to collect a set of recent advances and
results in these related topics, provide a platform for researchers to
exchange their innovative ideas on big modeling and computing solutions for
multimedia content analytics, and introduce interesting utilizations of
modeling and computing algorithms for particular social/personal media
applications, this special issue will target emergent big modeling and
computing methods for multimedia signal processing and understanding (with
a special focus on social media and personal data).

To summarize, this special issue welcomes a broad range of submissions on
the development and use of artificial intelligence and computing techniques
for multimedia analytics. We are especially interested in: 1) theoretical
advances as well as algorithm developments in big data technology for
specific social/personal media analytics problems; 2) reports of practical
applications and system innovations in social/personal media analytics; and
3) novel datasets as test beds for new developments, preferably with
implemented standard benchmarks. The following list suggests (but is not
limited to) possible topics of interest:

·                          Big Data Technology Specifically for Multimedia
Analytics
·                          Big Data Technology for Multimedia Annotation,
Tagging and Classification
·                          Big Data Technology for Multimedia Abstraction
and Summarization
·                          Big Data Technology for Multimedia Indexing and
Retrieval
·                          Big Data Technology and Computing for Social
Media Analytics
·                          Big Data Technology and Computing for Biological
Data
·                          Big Data Technology and Computing for Personal
Data Mining
·                          Modeling of Wearable Device Sensor Streams
·                          Personal Data based Social Network Analysis and
Web Mining
·                          Cloud Computing for Social Intelligence and
Personal Data
·                          Deep Learning for Social Media Analytics
·                          Deep Learning for Security in Social Media
Important dates:

Manuscript Submission: May 01, 2015
Initial Decision: August 01, 2015
R1 Version: October 01, 2015
Acceptance Notification: November 01, 2015
Final Manuscripts Due: November 15, 2015
Anticipated Publication: January 01, 2016

Submission:

Manuscripts (Please follow Signal Processing publishing format, details can
be found athttp://www.elsevier.com/
journals/signal-processing/0165-1684/guide-for-authors) should be submitted
via the Electronic Editorial System of Elsevier:
http://ees.elsevier.com/sigpro/. Please make sure to select the "SI: BDMA"
as Article Type during the submission process.
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