DC Field | Value | Language |
---|---|---|
dc.contributor.author | Min, Hwang-Ki | ko |
dc.contributor.author | Hou, Yuxi | ko |
dc.contributor.author | Park, Sangwoo | ko |
dc.contributor.author | Song, Iickho | ko |
dc.date.accessioned | 2016-04-20T06:07:22Z | - |
dc.date.available | 2016-04-20T06:07:22Z | - |
dc.date.created | 2015-12-22 | - |
dc.date.created | 2015-12-22 | - |
dc.date.created | 2015-12-22 | - |
dc.date.issued | 2016-02 | - |
dc.identifier.citation | PATTERN RECOGNITION, v.50, pp.45 - 55 | - |
dc.identifier.issn | 0031-3203 | - |
dc.identifier.uri | http://hdl.handle.net/10203/205094 | - |
dc.description.abstract | The kernel discriminant analysis (KDA), an extension of the linear discriminant analysis (LDA) and null space-based LDA into the kernel space, generally provides good pattern recognition (PR) performance for both small sample size (SSS) and non-SSS PR problems. Due to the eigen-decomposition technique adopted, however, the original scheme for the feature extraction with the KDA suffers from a high complexity burden. In this paper, we derive a transformation of the KDA into a linear equation problem, and propose a novel scheme for the feature extraction with the KDA. The proposed scheme is shown to provide us with a reduction of complexity without degradation of PR performance. In addition, to enhance the PR performance further, we address the incorporation of regularization into the proposed scheme. | - |
dc.language | English | - |
dc.publisher | ELSEVIER SCI LTD | - |
dc.title | A computationally efficient scheme for feature extraction with kernel discriminant analysis | - |
dc.type | Article | - |
dc.identifier.wosid | 000364893700004 | - |
dc.identifier.scopusid | 2-s2.0-84946532450 | - |
dc.type.rims | ART | - |
dc.citation.volume | 50 | - |
dc.citation.beginningpage | 45 | - |
dc.citation.endingpage | 55 | - |
dc.citation.publicationname | PATTERN RECOGNITION | - |
dc.identifier.doi | 10.1016/j.patcog.2015.08.021 | - |
dc.contributor.localauthor | Song, Iickho | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Kernel discriminant analysis | - |
dc.subject.keywordAuthor | Computational complexity | - |
dc.subject.keywordAuthor | Lagrange method | - |
dc.subject.keywordAuthor | Regularization | - |
dc.subject.keywordAuthor | Pattern recognition | - |
dc.subject.keywordPlus | SAMPLE-SIZE PROBLEM | - |
dc.subject.keywordPlus | COMPONENT ANALYSIS | - |
dc.subject.keywordPlus | FACE RECOGNITION | - |
dc.subject.keywordPlus | LDA | - |
dc.subject.keywordPlus | IMPLEMENTATION | - |
dc.subject.keywordPlus | PARAMETER | - |
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