IEEE Workshop on Neural Networks for Signal Processing - NNSP 2003, Toulouse (France). 17-19 September 2003
Summary:
While reading handwritten text accurately is a difficult task for computers, the conversion of handwritten papers into digital format is necessary for automatic processing. Since most bank checks are handwritten, the number of checks is very high, and manual processing involves significant expenses, many banks are interested in systems that can read check automatically. This paper presents several approaches to improve the accuracy of neural networks used to read unconstrained numerals in the courtesy amount field of bank checks.
Keywords: Optical character recognition, neural networks, document imaging, check processing, unconstrained handwritten numerals.
DOI: 
https://doi.org/10.1109/NNSP.2003.1318060
Published in NNSP 2003, pp: 607-616, ISBN: 0-7803-8177-7
Publication date: 2004-08-02.
Citation:
R. Palacios, A. Gupta, Training Neural Networks for Reading Handwritten Amounts on Checks, IEEE Workshop on Neural Networks for Signal Processing - NNSP 2003, Toulouse (France). 17-19 September 2003. In: NNSP 2003: Conference proceedings, ISBN: 0-7803-8177-7
