Connectionists: Information Fusion Journal Special Issue

[M.Casey@surrey.ac.uk]

Call for papers for a special issue of the journal Information Fusion on
"Biologically Inspired Information Fusion"

Deadline for Submission: January 30, 2007

Full details at
http://www.elsevier.com/authored_subject_sections/P05/CFP/IFJ_CFP_IDS.pd
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Bringing together research on the biology and psychology of
multi-sensory processing, computational neuroscience and theoretical
work on mechanisms for combining different information sources.

Topics appropriate for this special issue include, but are not limited
to:
* Biologically inspired fusion schemes
* Adaptive information fusion which emphasize biological motivations
* Biologically inspired fusion in robotics
* Multimodal integration:
  * Modeling combined sensory processing
  * Including, but not exclusively, combining vision, audition,
olfaction, taste or touch
  * Combining artificial and biological sensors
  * Attention or emotional biasing on sensory processing
* Biologically motivated applications of multi-sensor integration

Our understanding of both natural and artificial cognitive systems is an
exciting area of research that is developing into a multi-disciplinary
subject with the potential for significant impact on science,
engineering and society in general. There is considerable interest in
how our understanding of natural systems may help us to apply biological
strategies to artificial systems. Of particular interest is our
understanding of how to build adaptive information fusion systems by
combining knowledge from different domains. In natural systems, the
integration of sensory information is learnt at an early stage of
development. Therefore, through a better understanding of the structures
and processes involved in this natural adaptive integration, we may be
able to construct a truly artificial multi-sensory processing system.
Here then, psychological and physiological knowledge of multisensory
processing, and particularly the low level influence that different
modalities have on one another, can be used to build upon existing
theoretical work on computational mechanisms, such as self organization
and the combination of multiple neural networks, to build systems that
can fuse together different information sources.

These themes were recently discussed at an International Workshop on
Biologically Inspired Information Fusion. As well as presenting the
state-of-the-art on multi-sensory processing and information fusion from
the life and physical sciences, the workshop provided a forum for
researchers to discuss priorities for developing this multi-disciplinary
area. This special issue of Information Fusion is therefore aimed at
following up from these discussions by focusing on the highlighted
priorities, whilst also providing an opportunity for the wider
dissemination of relevant themes. For this special issue, papers should
either have a biological motivation and/or inspiration, or otherwise be
of biological relevance and interest. Manuscripts should make the
biological dimension explicit. Information Fusion related papers lacking
this dimension are to be submitted to a regular issue of the journal.

Manuscripts (which should be original and not previously published or
presented even in a more or less similar form under any other forum)
covering biologically inspired information fusion methods and their
applications as well as the theories and algorithms developed to address
these applications are invited. Contributions should be described in
sufficient detail to be reproducible on the basis of the material
presented in the paper.

Manuscripts should be submitted electronically online at
http://ees.elsevier.com/inffus. The corresponding author will have to
create a user profile if one has not been established before at
Elsevier. Simultaneously, please also send without fail an electronic
copy (PDF format preferred), to the Guest Editors listed below. Please
identify clearly that the submission is meant for this special issue.

Guest Editors
Dr Matthew Casey, Department of Computing, University of Surrey, UK,
m.casey at surrey.ac.uk
Professor Robert Damper, School of Electronics and Computer Science,
University of Southampton, UK, rid at ecs.soton.ac.uk

Further information can be found at:

http://www.cs.surrey.ac.uk/people/academic/M.Casey/biif2006.html
http://www.elsevier.com/locate/inffus