Call for Papers
 IEEE Transaction on Neural Networks
 Special Issue on Intelligent Multimedia Processing
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Human communication is intrinsically multi-modal. With the advances of
 technology, modern communication systems will also become more and more

 multi-modal. 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 multi-modal signals. This is
particularly
 emphasised 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 multi-modality.

 Intelligent multimedia processing shares three fundamental goals with
 biological systems: a) Universal data processing engine
 for multi-modal signals; b) Multi-modality; 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 optimisation techniques.
 In addition, spatial/temporal neural structures and hierarchical models

 are promising for multi-rate, multi-resolution 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.
 * Multi-modal 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 categorisation,
   interactive human-machine vision, speech recognition, speaker
   recognition, gesture analysis and recognition, auditory/visual scene
   analysis, and multi-modal interaction.
 * Multimedia data analysis and visualisation: texture, colour, 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:   Jan 15, 2001
      Acceptance notification: June 15, 2001
      Final manuscripts due:   July 31, 2001
      Publication:             November 2001


 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