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18th International Conference on Pattern Recognition (ICPR'06) Volume 3
Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
ASCII Text
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Eugen Barbu, Romain Raveaux, Herve Locteau, Sebastien Adam, Pierre Heroux, Eric Trupin, "Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition," Pattern Recognition, International Conference on, vol. 3, pp. 296-299, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006.
 
 
BibTex
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@article{ 10.1109/ICPR.2006.612,
author = {Eugen Barbu and Romain Raveaux and Herve Locteau and Sebastien Adam and Pierre Heroux and Eric Trupin},
title = {Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition},
journal ={Pattern Recognition, International Conference on},
volume = {3},
year = {2006},
issn = {1051-4651},
pages = {296-299},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.612},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition
SN - 1051-4651
SP296
EP299
A1 - Eugen Barbu,
A1 - Romain Raveaux,
A1 - Herve Locteau,
A1 - Sebastien Adam,
A1 - Pierre Heroux,
A1 - Eric Trupin,
PY - 2006
KW - null
VL - 3
JA - Pattern Recognition, International Conference on
ER -
 
Eugen Barbu, LITIS Labs - University of Rouen, FRANCE
Romain Raveaux, LITIS Labs - University of Rouen, FRANCE
Herve Locteau, LITIS Labs - University of Rouen, FRANCE
Sebastien Adam, LITIS Labs - University of Rouen, FRANCE
Pierre Heroux, LITIS Labs - University of Rouen, FRANCE
Eric Trupin, LITIS Labs - University of Rouen, FRANCE
We present in this paper a graph classification approach using genetic algorithm and a fast dissimilarity measure between graphs called graph probing. The approach consists in the learning of a set of synthetic graph prototypes which are used for a 1NN classification step. Some experiments are performed on real data sets, representing 10 symbols. These tests demonstrate the interest to produce prototypes instead of finding representatives which simply belong to the data set.
Citation:
Eugen Barbu, Romain Raveaux, Herve Locteau, Sebastien Adam, Pierre Heroux, Eric Trupin, "Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition," icpr, vol. 3, pp.296-299, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006
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