DBN Fusion Model for Offline Handwritten Chinese Characters Ｒecognition
The requirement of the recognition result is also increasing in practical applications. In this paper，a new classifier cascade recognition model is proposed for the problem of offline handwritten Chinese character recognition. New model is the fusion of modified quadratic discriminant function ( M...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2017-12-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1459 |
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| Summary: | The requirement of the recognition result is also increasing in practical applications. In this paper，a
new classifier cascade recognition model is proposed for the problem of offline handwritten Chinese character
recognition. New model is the fusion of modified quadratic discriminant function ( MQDF) and deep belief network
( DBN) . First to recognize and get result using MQDF，and calculate the reliability of the recognition result. If the
reliability can meet the requirement，MQDF recognition result can be as the final result directly output. Otherwise
using the DBN to make recognition again and getting the final recognition result. Experiments show that the MQDF
and DBN fusion model proposed in this paper can achieve better accuracy than the single use of MQDF and DBN in
the offline handwritten Chinese character recognition task，which is performed on the ETL-9B handwritten Chinese
character dataset. |
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| ISSN: | 1007-2683 |