標題: Multilinguistic handwritten character recognition by Bayesian decision-based neural networks
作者: Fu, HC
Xu, YY
資訊工程學系
Department of Computer Science
關鍵字: Bayesian decision-based neural networks;optical character recognition;self-growing probabilistic decision-based neural networks;supervised learning
公開日期: 1-Oct-1998
摘要: In this paper, we present a Bayesian decision-based neural network (BDNN) for multilinguistic handwritten character recognition, The proposed self-growing probabilistic decision-based neural network (SPDNN) adopts a hierarchical network structure with nonlinear basis functions and a competitive credit-assignment scheme, Our prototype system demonstrates a successful utilization of SPDNN to the handwriting of Chinese and alphanumeric character recognition on both public databases (CCL/HCCR1 for Chinese and CEDAR for the alphanumerics) and in-house database (NCTU/NNL), Regarding the performance, experiments on three different databases all demonstrated high recognition (86-94%) accuracy as well as low rejection/acceptance (6.7%) rates. As for the processing speed, the whole recognition process (including image preprocessing, feature extraction, and recognition) consumes approximately 0.27 s/character on a Pentium-100 based personal computer, without using a hardware accelerator or coprocessor.
URI: http://dx.doi.org/10.1109/78.720379
http://hdl.handle.net/11536/31828
ISSN: 1053-587X
DOI: 10.1109/78.720379
期刊: IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume: 46
Issue: 10
起始頁: 2781
結束頁: 2789
Appears in Collections:Articles


Files in This Item:

  1. 000076095000018.pdf