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dc.contributor.authorKasabov, Nikolaen_NZ
dc.contributor.authorIsrael, Stevenen_NZ
dc.contributor.authorWoodford, Brendon Jen_NZ
dc.date.available2011-04-07T03:05:49Z
dc.date.copyright1999-05en_NZ
dc.identifier.citationKasabov, N., Israel, S., & Woodford, B. J. (1999). Adaptive, evolving, hybrid connectionist systems for image pattern recognition (Information Science Discussion Papers Series No. 99/08). University of Otago. Retrieved from http://hdl.handle.net/10523/964en
dc.identifier.urihttp://hdl.handle.net/10523/964
dc.descriptionPlease note that this is a searchable PDF derived via optical character recognition (OCR) from the original source document. As the OCR process is never 100% perfect, there may be some discrepancies between the document image and the underlying text. Searching and selecting the text of this PDF may also not work in all viewers; for example, they have been found to not work in Apple's Preview application. We therefore recommend Adobe Reader for viewing and searching this PDF.en_NZ
dc.description.abstractThe chapter presents a new methodology for building adaptive, incremental learning systems for image pattern classification. The systems are based on dynamically evolving fuzzy neural networks that are neural architectures to realise connectionist learning, fuzzy logic inference, and case-based reasoning. The methodology and the architecture are applied on two sets of real data—one of satellite image data, and the other of fruit image data. The proposed method and architecture encourage fast learning, life-long learning and on-line learning when the system operates in a changing environment of image data.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherUniversity of Otagoen_NZ
dc.relation.ispartofseriesInformation Science Discussion Papers Seriesen_NZ
dc.subjectimage classificationen_NZ
dc.subjectcase-based reasoningen_NZ
dc.subjectEvolving Fuzzy Neural Networksen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleAdaptive, evolving, hybrid connectionist systems for image pattern recognitionen_NZ
dc.typeDiscussion Paperen_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages21en_NZ
otago.date.accession2010-12-15 19:43:16en_NZ
otago.schoolInformation Scienceen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints990en_NZ
otago.school.eprintsKnowledge Engineering Laboratoryen_NZ
otago.school.eprintsInformation Scienceen_NZ
otago.school.eprintsSurveyingen_NZ
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otago.relation.number99/08en_NZ
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