CFP: Neural Networks on Shape Analysis
Vision List Digest:
Article 11,
Volume 12, Issue 9
From: sull@stereo.csl.uiuc.edu (Sanghoon Sull)
Post-Followup: submission@VISLIST.com
CALL FOR PAPERS
Progress In Neural Networks
Special Volume on Shape Analysis
Omid M. Omidvar Minsoo Suk
Series Editor Volume Editor
Significant progress has been made recently in shape analysis using
neural networks and the energy minimization concept. Ablex Publishing
Corporation is planning a special volume on "Shape Analysis", scheduled
for this year.
This volume will be a part of "Progress in Neural Networks," an annual
book series reviewing research in modelling, analysis, design and
application of neural networks. The primary aim of this volume is to
present, in a single volume, the most important achievements made on
this important topic, which are otherwise scattered in diverse literature.
Authors are invited to submit original manuscripts detailing recent
progress. Suggested topics include, but are not limited to: shape modelling,
shape estimation, shape recovery, shape representation, shape matching,
surface reconstruction and surface decomposition. Research work utilizing
neural networks directly or based on energy minimization techniques such as
Markov random field, mean field annealing, simulated annealing, graduated
non-convexity algorithms and resistive networks are most welcome.
The paper should be tutorial in nature, self contained and preferably,
but not necessarily, about fifty double spaced pages in length. Please send
electronically (if you prefer, you can send a hardcopy to the address below)
an abstract and an outline msuk@ima.enst.fr
by May 30, 1993. The full paper
must be submitted by July 31, 1993 to:
Europe USA
Professor Minsoo Suk Professor Omid M. Omidvar
Department IMAGES Computer Science Department
Ecole Nationale Superieure University of District of Columbia
des Telecommunications 4200 Connecticut Ave. N.W.
46, rue Barrault Washington D.C. 20008
75634 PARIS CEDEX 13 Phone: (202)282-7345
FRANCE Fax: (202)282-3677
Fax:33-1-45-81-37-94 email: oomidvar@udcvax.bitnet
email:msuk@ima.enst.fr
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