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Vector Model Based Indexing and Retrieval of Handwritten Medical Forms
Curitiba, Parana, Brazil September 23-September 26
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.262Ninth International Conference on Doc ...
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H. Cao, V. Govindaraju, "Vector Model Based Indexing and Retrieval of Handwritten Medical Forms," Document Analysis and Recognition, International Conference on, vol. 1, pp. 88-92, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007.
 
 
BibTex
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@article{ 10.1109/ICDAR.2007.262,
author = {H. Cao and V. Govindaraju},
title = {Vector Model Based Indexing and Retrieval of Handwritten Medical Forms},
journal ={Document Analysis and Recognition, International Conference on},
volume = {1},
year = {2007},
issn = {1520-5363},
pages = {88-92},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.262},
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 - Vector Model Based Indexing and Retrieval of Handwritten Medical Forms
SN - 1520-5363
SP88
EP92
A1 - H. Cao,
A1 - V. Govindaraju,
PY - 2007
VL - 1
JA - Document Analysis and Recognition, International Conference on
ER -
 
H. Cao, University at Buffalo, Amherst, NY
V. Govindaraju, University at Buffalo, Amherst, NY
A vector model based information retrieval of handwrit- ten medical forms is presented in this paper. In order to im- prove the IR performance on the erroneous output of hand- writing recognition (HR) systems, a variation of the vec- tor model is made to estimate the number of occurrences of terms from word segmentation and recognition proba- bilities. IR Tests show that our approach outperforms the retrieval of ordinary HR text in terms of mean average pre- cision (MAP), R-Precision, and interpolated 11-point pre- cisions.
Citation:
H. Cao, V. Govindaraju, "Vector Model Based Indexing and Retrieval of Handwritten Medical Forms," icdar, vol. 1, pp.88-92, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007
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