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DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 1550 | - |
dc.citation.number | 11 | - |
dc.citation.startPage | 1542 | - |
dc.citation.title | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
dc.citation.volume | 24 | - |
dc.contributor.author | Kim, Kwang In | - |
dc.contributor.author | Jung, Keechul | - |
dc.contributor.author | Park, Se Hyun | - |
dc.contributor.author | Kim, Hang Joon | - |
dc.date.accessioned | 2023-12-22T11:36:32Z | - |
dc.date.available | 2023-12-22T11:36:32Z | - |
dc.date.created | 2019-02-25 | - |
dc.date.issued | 2002-11 | - |
dc.description.abstract | This paper investigates the application of support vector machines (SVMs) in texture classification. Instead of relying on an external feature extractor, the SVM receives the gray-level values of the raw pixels, as SVMs can generalize well even in high-dimensional spaces. Furthermore, it is shown that SVMs can incorporate conventional texture feature extraction methods within their own architecture, while also providing solutions to problems inherent in these methods. One-against-others decomposition is adopted to apply binary SVMs to multitexture classification, plus a neural network is used as an arbitrator to make final classifications from several one-against-others SVM outputs. Experimental results demonstrate the effectiveness of SVMs in texture classification. | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, v.24, no.11, pp.1542 - 1550 | - |
dc.identifier.doi | 10.1109/TPAMI.2002.1046177 | - |
dc.identifier.issn | 0162-8828 | - |
dc.identifier.scopusid | 2-s2.0-0036858347 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/26219 | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/1046177 | - |
dc.identifier.wosid | 000178846400012 | - |
dc.language | 영어 | - |
dc.publisher | IEEE COMPUTER SOC | - |
dc.title | Support vector machines for texture classification | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic | - |
dc.relation.journalResearchArea | Computer Science; Engineering | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | support vector machines | - |
dc.subject.keywordAuthor | texture analysis | - |
dc.subject.keywordAuthor | pattern classification | - |
dc.subject.keywordAuthor | machine learning | - |
dc.subject.keywordAuthor | feature extraction | - |
dc.subject.keywordPlus | SEGMENTATION | - |
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