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Conference Paper: Novel design of neural networks for handwritten Chinese character recognition

TitleNovel design of neural networks for handwritten Chinese character recognition
Authors
KeywordsHandwritten Chinese character recognition
Neural networks
ETL9B
Issue Date1998
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/app/Publications/index.cfm?fuseaction=proceedings
Citation
Vision Geometry VII, San Diego, California, USA, 20-22 July 1998, v. 3454, p. 324-329 How to Cite?
AbstractHandwritten Chinese character recognition system invariably sue different image processing techniques to preprocess the input image before the main classification and recognition techniques are used. The authors proposed a different approach to the system philosophy of solving the handwritten Chinese character recognition problem for no preprocessing is necessary. The Chinese characters are treat as ideographs. The proposed system comprise of a Rough Classifier which control the different Fine Classifiers. Each classifier is an optimized artificial neural network using genetic algorithms. A reduced system has been implemented. The result shows that the proposed system has higher recognition rate than the similar systems reported and is more efficiency.
Persistent Identifierhttp://hdl.handle.net/10722/46582
ISSN

 

DC FieldValueLanguage
dc.contributor.authorYip, HFDen_HK
dc.contributor.authorYu, WWHen_HK
dc.date.accessioned2007-10-30T06:53:24Z-
dc.date.available2007-10-30T06:53:24Z-
dc.date.issued1998en_HK
dc.identifier.citationVision Geometry VII, San Diego, California, USA, 20-22 July 1998, v. 3454, p. 324-329en_HK
dc.identifier.issn0277-786Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/46582-
dc.description.abstractHandwritten Chinese character recognition system invariably sue different image processing techniques to preprocess the input image before the main classification and recognition techniques are used. The authors proposed a different approach to the system philosophy of solving the handwritten Chinese character recognition problem for no preprocessing is necessary. The Chinese characters are treat as ideographs. The proposed system comprise of a Rough Classifier which control the different Fine Classifiers. Each classifier is an optimized artificial neural network using genetic algorithms. A reduced system has been implemented. The result shows that the proposed system has higher recognition rate than the similar systems reported and is more efficiency.en_HK
dc.format.extent258871 bytes-
dc.format.extent3380 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/app/Publications/index.cfm?fuseaction=proceedingsen_HK
dc.rightsS P I E - the International Society for Optical Proceedings. Copyright © S P I E - International Society for Optical Engineering.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsCopyright 1998 Society of Photo-Optical Instrumentation Engineers. This paper was published in Vision Geometry VII, San Diego, California, USA, 20-22 July 1998, v. 3454, p. 324-329 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en_HK
dc.subjectHandwritten Chinese character recognitionen_HK
dc.subjectNeural networksen_HK
dc.subjectETL9Ben_HK
dc.titleNovel design of neural networks for handwritten Chinese character recognitionen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0277-786X&volume=3454&spage=324&epage=329&date=1998&atitle=Novel+design+of+neural+networks+for+handwritten+Chinese+character+recognitionen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/12.323271en_HK
dc.identifier.scopuseid_2-s2.0-0037960118-
dc.identifier.hkuros47041-

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