Integrated segmentation and recognition of handwritten numerals with cascade neural network
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, SW | - |
dc.contributor.author | Kim, SY | - |
dc.date.accessioned | 2021-09-09T12:37:56Z | - |
dc.date.available | 2021-09-09T12:37:56Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 1999-05 | - |
dc.identifier.issn | 1094-6977 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/124418 | - |
dc.description.abstract | In this paper, we propose an integrated segmentation and recognition method using cascade neural network. In the proposed method, a new type of cascade neural network is del eloped to train the spatial dependences in connected handwritten numerals. This cascade neural network was originally extended from the multilayer feedforward neural network to improve the discrimination and generalization power. Tn order to verify the performance of the proposed method, recognition experiments with the National Institute of Standards and Technology (NIST) numeral databases have been performed. The experimental results reveal that the proposed method has higher discrimination and generalization power than the previous integrated segmentation and recognition (ISR) methods have. Moreover, the network-size of the proposed method Is smaller than that of previous integrated segmentation and recognition methods. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | WORD RECOGNITION | - |
dc.title | Integrated segmentation and recognition of handwritten numerals with cascade neural network | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, SW | - |
dc.identifier.doi | 10.1109/5326.760572 | - |
dc.identifier.scopusid | 2-s2.0-0032664317 | - |
dc.identifier.wosid | 000080105100011 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, v.29, no.2, pp.285 - 290 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS | - |
dc.citation.title | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS | - |
dc.citation.volume | 29 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 285 | - |
dc.citation.endPage | 290 | - |
dc.type.rims | ART | - |
dc.type.docType | Letter | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Cybernetics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.subject.keywordPlus | WORD RECOGNITION | - |
dc.subject.keywordAuthor | cascade neural network | - |
dc.subject.keywordAuthor | handwritten character recognition | - |
dc.subject.keywordAuthor | segmentation and recognition of numerals | - |
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