Integrated segmentation and handwritten characters with recognition of connected recurrent neu.ra1 network

Seong Whan Lee, Eung Jae Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In this paper, we propose an integrated segmentation and recognition method for recognizing connected handwritten characters with recurrent neural network. It has been developed to both integrate segmentation and recognition within a single recurrent neural network and recognize connected handwratten characters using the spatial dependencies in the images of connected handwritten characters. In order to verify the performance of the proposed method, experiments with the NIST database have been carried out and the performance of the proposed method has been compared with those of the previous integrated segmentation and recognition methods.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995
PublisherIEEE Computer Society
Pages413-416
Number of pages4
ISBN (Electronic)0818671289
DOIs
Publication statusPublished - 1995 Jan 1
Event3rd International Conference on Document Analysis and Recognition, ICDAR 1995 - Montreal, Canada
Duration: 1995 Aug 141995 Aug 16

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume1
ISSN (Print)1520-5363

Conference

Conference3rd International Conference on Document Analysis and Recognition, ICDAR 1995
CountryCanada
CityMontreal
Period95/8/1495/8/16

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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    Lee, S. W., & Lee, E. J. (1995). Integrated segmentation and handwritten characters with recognition of connected recurrent neu.ra1 network. In Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995 (pp. 413-416). [599025] (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR; Vol. 1). IEEE Computer Society. https://doi.org/10.1109/ICDAR.1995.599025