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dc.contributor.authorDeng, Daen_NZ
dc.contributor.authorKasabov, Nikolaen_NZ
dc.date.available2011-04-07T03:05:24Z
dc.date.copyright2000-11en_NZ
dc.identifier.citationDeng, D., & Kasabov, N. (2000). Evolving localised learning for on-line colour image quantisation (Information Science Discussion Papers Series No. 2000/16). University of Otago. Retrieved from http://hdl.handle.net/10523/885en
dc.identifier.urihttp://hdl.handle.net/10523/885
dc.description.abstractAlthough widely studied for many years, colour image quantisation remains a challenging problem. We propose to use an evolving self-organising map model for the on-line image quantisation tasks. Encouraging results are obtained in experiments and we look forward to implementing the algorithm in real world applications with further improvement.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherUniversity of Otagoen_NZ
dc.relation.ispartofseriesInformation Science Discussion Papers Seriesen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleEvolving localised learning for on-line colour image quantisationen_NZ
dc.typeDiscussion Paperen_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages8en_NZ
otago.date.accession2010-10-27 21:08:20en_NZ
otago.schoolInformation Scienceen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints980en_NZ
otago.school.eprintsKnowledge Engineering Laboratoryen_NZ
otago.school.eprintsInformation Scienceen_NZ
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otago.relation.number2000/16en_NZ
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