TNN Special Issue Final Call for Papers

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Final Call for Papers
IEEE Transaction on Neural Networks
Special Issue on Intelligent Multimedia Processing

Human communication is intrinsically multimodal. With the advances of
technology, modern communication systems will also become more and more
multimodal. Hence, multimedia technologies represent new ground for
research interactions among a variety of media such as speech, audio, image,
video, text and graphics. Future multimedia technologies will need to handle
information with an increasing level of intelligence, i.e., automatic
recognition and interpretation of multimodal signals. This is particularly
emphasized in MPEG-7 which focuses on the 'multimedia content description
interface'. The description shall be associated with the content itself to
facilitate fast and effective searching for all the media. Specifically, 
the MPEG-7 research domain will cover techniques for content-based indexing
and retrieval: pattern recognition, face detection/recognition, and fusion
of multimodality.

Intelligent multimedia processing shares three fundamental goals with
biological systems: a) Universal data processing engine
for multimodal signals; b) Multimodality; and c) Unsupervised clustering
and/or supervised learning by examples. Because of these features,
neural networks are attractive candidates for intelligent multimedia
processing and recent activity in the area is a proof of this fact. The
main attribute of neural computing is its adaptive learning capability,
which enables interpretations of possible variations of a same object
or pattern, e.g., with respect to scale, orientation, and perspective.
Moreover, they are able to accurately approximate unknown systems based
on sparse sets of noisy data. Certain neural models also effectively
incorporate statistical signal processing and optimization techniques.
In addition, spatial/temporal neural structures and hierarchical models
are promising for multirate, multiresolution multimedia processing. As a 
result, many successful applications of neural networks in intelligent
multimedia processing, sometimes combined with fuzzy systems and evolutionary
computing, have been reported.

The possible topics for the special issue include, but are not limited to,
the following:

* Neural networks (including BSS and ICA) and other computational intelligence
  models, learning paradigms, and architectures for multimedia processing.
* Intelligent multimedia processing architectures.
* Multimedia/multichannel data fusion.
* Multimodal representation and information retrieval: Applications in
  hyperlinking of multimedia objects, query and search of multimedia
  information including intelligent web agents, 3D object representation
  and motion tracking, image sequence generation and animation.
* Human-computer interaction and communications: face recognition,
  lip-reading analysis, facial expression and emotion categorization,
  interactive human-machine vision, speech recognition, speaker
  recognition, gesture analysis and recognition, auditory/visual scene
  analysis, and multimodal interaction.
* Multimedia data analysis and visualization: texture, color, content, etc.
* Intelligent network control of audio/video streams in multimedia
  networking applications.

Original, previously-unpublished research articles as well as
state-of-the-art tutorial papers will be considered.  Authors should
follow the IEEE TNN manuscript format described in the Information for
Authors, which can be found on the inside back cover of any issue of
TNN. Prospective authors are invited to submit papers to the website:
http://eivind.imm.dtu.dk/tnn.

The following schedule will apply:

     Manuscript submission:   April 15, 2001
     Acceptance notification: July 31, 2001
     Final manuscripts due:   October 30, 2001
     Publication:             January 2002


Guest Editors:

Tulay Adali,                         Ling Guan,
Dept of CSEE                         School of Electrical & Information Eng.
Univ of Maryland, Baltimore County   The University of Sydney
Baltimore, MD 21250                  Sydney, NSW 2000
                                     Australia

Jan Larsen                           Shigeru Katagiri
Dept of Mathematical Modelling       ATR
Technical University of Denmark      2-2 Hikaridai
2800 Lyngby                          Seika-cho, Soraku-gun
Denmark                              Kyoto 619-02 Japan

                    Jose Principe
                    Dept of Electrical & Computer Eng
                    University of Florida
                    Gainesville, FL 32611