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A Multi-Agent System for Hand-drawn Diagram Recognition
Curitiba, Parana, Brazil September 23-September 26
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.21Ninth International Conference on Doc ...
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G. Casella, V. Deufemia, V. Mascardi, "A Multi-Agent System for Hand-drawn Diagram Recognition," Document Analysis and Recognition, International Conference on, vol. 2, pp. 739-743, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2, 2007.
 
 
BibTex
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@article{ 10.1109/ICDAR.2007.21,
author = {G. Casella and V. Deufemia and V. Mascardi},
title = {A Multi-Agent System for Hand-drawn Diagram Recognition},
journal ={Document Analysis and Recognition, International Conference on},
volume = {2},
year = {2007},
issn = {1520-5363},
pages = {739-743},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.21},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Document Analysis and Recognition, International Conference on
TI - A Multi-Agent System for Hand-drawn Diagram Recognition
SN - 1520-5363
SP739
EP743
A1 - G. Casella,
A1 - V. Deufemia,
A1 - V. Mascardi,
PY - 2007
VL - 2
JA - Document Analysis and Recognition, International Conference on
ER -
 
G. Casella, Universit? di Genova
V. Deufemia, Universit? di Salerno
V. Mascardi, Universit? di Salerno
In this paper we present AgentSketch, an agent- based system for on-line recognition of hand-drawn diagrams. Agents are used for managing the activity of symbol recognizers and for providing efficient interpretations of the sketch to the user thanks to the use of contextual information for ambiguity resolution. The system can be applied to a variety of domains by providing recognizers of the symbols in that domain. A first experimental evaluation has been performed on the domain of UML use case diagrams to verify the effectiveness of the proposed approach.
Citation:
G. Casella, V. Deufemia, V. Mascardi, "A Multi-Agent System for Hand-drawn Diagram Recognition," icdar, vol. 2, pp.739-743, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2, 2007
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