Invited sessions
Call for participation to following invited sessions
:
Interested and qualified individuals are invited to
participate in the conference by organising and chairing invited sessions. Each
invited session must have 4 to 6 paper presentations. The organizers of these
sessions will be responsible for soliciting the presenters of invited papers
(in agreement with the Technical Program Committee Chairman). All accepted
invited papers are expected to be presented at the conference. Accepted
proposals will be put on these web pages to help organizers to promote their
own sessions.
Deadline for invited session proposals :
March 31st, 2000
Mail your proposal to Professor Roger Reynaud at :
secretariat@fusion2000.ief.u-psud.fr.
Proposal requirements
a - name and address (+ E-mail) of proposer,
b - short biography of proposer,
c - title of session,
d - a 100-word description of the topic of the session (E-mail
submissions only),
e - by the deadline (March 31st) , you HAVE also to provide to R.
Reynaud the abstracts of each invited paper (all invited session proposal
without abstract will be cancelled).
Note : If you plan to submit a proposal, please do not wait
for the deadline to submit requirements a-d. In such a way, your
info will be put online without delay which gives more chance for you to make
your invited session proposal successful (i.e. to satisfy requirement
e).
Final papers due for invited sessions
(no delay allowed) : May 15th, 2000 .
Prospective authors for invited sessions are invited to
submit their abstract DIRECTLY to the proposer of the sessions they want to
participate.
Data fusion in industry 
Chair: Mark Bedworth (University of Central
England / Jemity)
Email: mark.bedworth@datafusion.clara.co.uk
Session description
During the past five years the field of data fusion has been increasingly taken
up outside the defence community. There is now considerable interest in data
fusion for industrial applications Amongst others the use of data fusion is now
becoming established in the aerospace, manufacturing and condition monitoring
areas. The session seeks to bring together practitioners of data fusion in
these and related industrial fields to show how the technology can be applied
to real problems and used to make genuine (and marketable) improvements to
processes and products.
Brief biography
Dr. Mark Bedworth is a Fellow of the University of Central
England in Birmingham, UK and co-director of a small data fusion consultancy
company. Prior to 1999 he worked for the UK government for 15 years during
which time he both conducted and lead scientific research into data fusion and
related topics. He was a member of the UK Government's working group on Data
Fusion in 1996 which examined the potential impact of data fusion in UK
industry. He is a director of the International Society for Information Fusion.
Hybrid approaches to information fusion:
integration of symbolic and numeric information
Galina L. Rogova, PhD
CUBRC
P.O.Box 400
Buffalo, NY 14225
Phone: 716-631-6741 - Fax: 716-631-4166
e-mail: rogova@cubrc.org
Session description
The goal of this session is to discuss advances in fusion of symbolic and
numeric information. Combination of symbolic and numeric information is
especially important for pattern and context processing that has strong
reliance on numeric characteristics, historic database, and expert opinions and
experience. Hybrid information processing requires integration of concepts from
numerical-algorithm-oriented methods, knowledge based systems, Fuzzy Logic,
Bayesian and evidential reasoning, and neural computing. The session will focus
on fundamental aspects of processing of symbolic and numeric data, architecture
of intelligent hybrid systems, and applications of hybrid methods to solution
of military as well as non-military problem
Brief biography
Galina L. Rogova received both her MS and PhD in Moscow,
Russia. Currently she is a scientist at Veridian Corporation and conducts her
research at CUBRC, a not-for-profit joint venture between SUNY at Buffalo and
Veridian Engineering. Her research interest is focused on hybrid approaches to
information fusion, decision fusion and decision support, pattern recognition
and medical imaging.
Data Fusion systems evaluation and test-beds
Chair: Uri Degen (POB 58180 Tel-Aviv 61581,
ISRAEL)
Email: udegen@atl.co.il
Session description
The goal of this session is to discuss different approaches to evaluation of
various aspects of the Data Fusion systems - sensor suites, algorithms and
systems as a whole. Both evaluation methodologies and tools will be addressed
in the session. Particular attention will be devoted to the emerging field of
Data Fusion test-beds, successfully used as a primary technology of the Data
Fusion systems evaluation. Comparison between alternative solutions, either
algorithmic or architectural, of the same Data Fusion problem, will be another
issue of interest for the session.
Brief biography
Dr. Uri Degen received his MSc in Physics from Kiev's State
University, USSR, and his PhD in Operations Research from Pacific Western
University, USA. Currently he manages Operations Research and Scientific
Systems unit in Advanced Technology Ltd. (ATL), Israel - see
http://www.atl.co.il. His professional
interest and main field of activity is focused on Data Fusion, in particular
Multi Sensor Tracking, systems evaluation and development. At the FUSION98
Conference he chaired the session "Practical Aspects of Data Fusion for
Air Surveillance".
Sensor Management and Adaptive Data Fusion
Dan Strömberg
FOA Swedish National Defense Research Establishment
Division of Command & Control Warfare Systems
P.O.Box 1165
S-581 11 Linkoping - SWEDEN
Telephone: +46 13 37 82 35 - E-mail: danstr@lin.foa.se
Session description
Currently there is a growing interest in adaptive data fusion and sensor
management. The flexibility of new and distributed sensor systems, applications
with large number of tasks requiring instantaneous resource allocation, and the
great number of non-trivial considerations influencing the allocation of
resources to sensor tasks, result in the need for improved insights into
intelligent methods for sensor control and process management. Issues include
task prioritization, planning and scheduling. This is a non-mature part of the
data fusion process, which eventually will improve the ways to allocate sensor
resources to sensor tasks. We invite researchers and practitioners with
interest, experiences and ideas in these and other control-related data fusion
issues.
Brief biography
Dan Strömberg received his Licentiate of Technology degree
from Computer Science Department in Linköping in 1987. Earlier activities
include an electrical engineering education. Currently he is at the Swedish
Defence Research Establishment (FOA) in Linköping, Sweden, where he
manages some airspace related research activities. Data fusion related
interests range from decision support to situation assessment, tracking and
sensor management. He has published a large number of papers and chaired
sessions in international computer science conferences.
Fuzzy
mathematical programming for fusion
Associate Professor Mustafa Gunes
University of Dokuz Eylul
Fac. of Economic & Adm. Sciences
Dept. Of Econometrics & Operational Research
Buca - Izmir - TURKEY
e.mail : mgunes@sifne.iibf.deu.edu.tr
Session description
Fuzzy Logic offers several unique feature that make it a particularly good
choice for many control and optimization problems. Fuzzy Logic which does not
require precise inputs, is inherently robust and can process any reasonable
number of inputs but system complexity increases rapidly with more inputs and
outputs. Operational Research techniques such as Linear, Integer, Goal
programming has different types of inputs. The main purpose of those techniques
is to design optimal structure of the business problems. In application, all
decisions carrying out some ambiguity, so that application of Fuzzy Logic to
the Operational Research techniques is providing information fusion on many
alternative decison models. The main aim of this session to meet and
communicate the scientists working on this side of Fuzzy Logic around the
globe.
Brief biography
Dr. Gunes graduated from the department of Mathematic, Faculty
of Science University of Ege,1978. He has received his master degree from the
depart. of Computer Engineering of Ege University, Izmir,1984. He completed his
Doctoral Project on Operational Research and Optimization at the University of
Ottawa, Canada,1989. He has organized "National Econometrics and
Statistics Symposium", twice, and completed fourth session of it in May
1999. Dr. Gunes was also member of the organizing committee of the 51th session
of the International Statistical Association, held in TURKEY in 1998. At the
same time he was consultant of the Head of The Turkey State Statistical
Institute during last two years. Now , he and his small group, are working on
Fuzzy Logic in Turkey and trying to establish National Fuzzy logic Association
by consulting to the Father Of Fuzzy Logic, Lofti Zadeh from USA.
Designing
for Data Fusion
Mark Bedworth
University of Central England / Jemity
e.mail : mark.bedworth@datafusion.clara.co.uk
Session description
There's no such thing as a "data fusion system" only systems with a
data fusion capability.
The multi-disciplined nature of data fusion makes it difficult to methodically
and systematically integrate into large systems. Of particular relevance to
this session are the following aspects of data fusion design:
- practicalities of system design,
- human factors,
- architectures,
- and design drivers.
The session aims to achieve a balance of issues (both
theoretical and practical) that will highlight the variety of problems to be
faced in designing for data fusion, give food for thought and (perhaps) provide
a few answers.
Brief biography
Dr. Mark Bedworth is a Fellow of the University of Central
England in Birmingham, UK and co-director of a small data fusion consultancy
company. Prior to 1999 he worked for the UK government for 15 years during
which time he both conducted and lead scientific research into data fusion and
related topics. He was a member of the UK Government's working group on Data
Fusion in 1996 which examined the potential impact of data fusion in UK
industry. He is a director of the International Society for Information Fusion.
Image Fusion & Exploitation
Allen M. Waxman, Ph.D.
Sensor Exploitation Group
MIT Lincoln Laboratory
244 Wood Street, Bldg.-S
Lexington, MA 02420-9185, USA
Email: WAXMAN@LL.MIT.EDU
Session description
This session will address various aspects of image fusion from one or more
sensors. Methodologies, applications, systems, and utility of image fusion will
all be addressed. We invite papers from both key investigators and agency
representatives addressing one or more of the following topics:
- multi-sensor image fusion in biological systems
- methodologies for registration and fusion of multi-sensor
imagery
- data mining of fused multi-sensor imagery
- construction of 3D site models from
multi-aspect/multi-sensor imagery
- utilization of 3D site models for multi-sensor image fusion
- fusion of 3D site models with live video imagery
- applications of image fusion to surveillance and navigation
- applications of image fusion to remote sensing of the earth
and planets
- applications of image fusion to medical imaging sensors
- object/target recognition from multi-sensor fused imagery
- web technologies for remote exploitation of multi-sensor
imagery
- perceptual issues in the utilization of fused imagery
- situational awareness using fused image displays
- government and industry programs/views on multi-sensor
image fusion
Brief biography
Allen M. Waxman is a Senior Staff member in the Sensor
Exploitation Group at MIT Lincoln Laboratory, where he directs a research team
focused on neural network modeling, multi-sensor fusion for surveillance,
pattern learning and recognition, and sensor fused night vision. He also holds
a joint appointment as an Adjunct Associate Professor in the Department of
Cognitive and Neural Systems at Boston University. He received a B.S. degree in
Physics from the City College of New York in 1973 and a Ph.D. degree in
Astrophysics from the University of Chicago in 1978. Prior to joining Lincoln
Laboratory in 1989, he performed research at MIT, the University of Maryland,
the Weizmann Institute of Science (Israel), the Royal Institute of Technology
(Sweden), and Boston University. In 1992 he was recipient of the Outstanding
Research Award from the International Neural Network Society for work on 3D
object learning and recognition. In 1996 he received the Best Paper Award from
the IRIS Passive Sensors Group for work on real-time image fusion for color
night vision. Current research efforts involve real-time multi-sensor image
fusion in conjunction with 3D site models and 3D imaging, interactive fused
image mining by trainable search agents, and client-server based exploitation
and dissemination of 3D fused sensor data. Dr. Waxman holds three U.S. patents
and has authored over eighty publications.
Last Updated: March 15, 2000
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