[image 00506] S+SSPR2014 (@Finland, 3/14投稿締切)

Seiichi Uchida uchida @ ait.kyushu-u.ac.jp
2014年 2月 23日 (日) 09:17:48 JST


image-MLの皆様:

九州大学の内田です.
毎回ICPRと同期して開催されているS+SSPRのCFP
をお送りいたします.重複受け取りの際はご容赦ください.

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                        CALL FOR PAPERS
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                          S+SSPR 2014

              IAPR Joint International Workshops on
      10th Statistical Techniques in Pattern Recognition (SPR)
  15th Structural and Syntactic Pattern Recognition Workshop (SSPR)

                       20-22 August 2014
                       Joensuu, Finland

                  http://cs.uef.fi/ssspr2014/

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IMPORTANT DATES:

Paper submission:   14 March  2014   (extended)
Notifications:      28 April  2014 Camera-ready:       17 May    2014

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CONFERENCE TOPICS:

We invite original contributions within the following topics:

SPR Topics:

Domain adaptation                    Structural Matching
Dissimilarity Representations        Structural Complexity
Ensemble Methods                     Syntactic Pattern Recognition
Multiple Classifiers                 Image Understanding
Gaussian Processes                   Shape Analysis
Dimensionality Reduction             Graph-theoretic Methods
Clustering Algorithms                Graphical Models
Model Selection                      Structural Kernels
Semi-Supervised Learning             Spectral Methods
Multiple Instance Learning           Spatio-Temporal Pattern Recognition
Active Learning                      Stochastic Structural Models
Contextual Pattern Recognition       Intelligent Sensing Systems
Location-based Pattern Recognition   Multimedia Analysis
Partially Supervised Learning        Structured Text Analysis
Novelty Detection                    Image Document Analysis
Comparative Studies

In addition to the original contributions, we also invite authors
to submit their recent papers (within 1 year) published in a related
journal (e.g. PAMI, PR, PRL, JMLR). These papers will undergo a lighter
review process, and if accepted, they will be included in the workshop
program and short abstract in the proceedings.

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PAPER SUBMISSION PROCEDURE:

All manuscripts (max. 10 pages) must be in LaTex format following
Springer's LNCS style:

http://www.springer.com/comp/lncs/authors.html

All papers are submitted via EasyChair, and will be reviewed
at least two or more anonymous reviewers. Accepted papers
(not exceeding 10 pages) will be published in Springer's
Lecture Notes in Computer Science (LNCS) series, providing
that at least one author will register to the workshop and
present the paper.

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KEYNOTE SPEAKERS:

Prof. Ali Shokoufandeh, Drexel University, Philadelphia, US
Approximation of hard combinatorial problems
via embedding to hierarchically separated trees
https://www.cs.drexel.edu/~ashokouf/

Prof. David Hand
Imperial College, London, UK
Evaluating supervised classification methods:
error rate, ROC curves, and beyond
http://www3.imperial.ac.uk/people/d.j.hand

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ORGANIZATION:

General Chair:
Pasi Fränti, University of Eastern Finland

SPR Chairs:
Gavin Brown, University of Manchester, UK
Marco Loog, Delft University of Technology, The Netherlands

SSPR Chairs:
Francisco Escolano, Universidad de Alicante, Spain
Marcello Pelillo, University of Venice, Italy

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VENUE:

The workshops are organized by School of Computing in the
University of Eastern Finland. Joensuu is a small town of
75,000 inhabitants in the lakeside Finland - the capital
of green. It is famous its peaceful nature, excellent
outdoor opportunities as well as many saunas.

TRAVEL:

Joensuu can be reached easiest from Helsinki (50 min transit),
which can be reached direct flights from most European cities,
New York, Chicago and all the major hubs in Asia including
Beijing, Shanghai, Tokio, Osaka, Bangkok and Singapore.

The workshops are organized one week prior to ICPR conference.
Schedude is planned to support smooth transit to Stockholm
either by flight or by a memorable sea cruise.

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LINKS:

http://cs.uef.fi/ssspr2014/
https://www.facebook.com/pages/SSSPR-2014/171649539698188

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-- 
Seiichi Uchida
uchida @ ait.kyushu-u.ac.jp
Kyushu University


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