Pattern recognition and the nondeterminable affine parameter problem

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dc.contributor.advisorMason, Scotten_ZA
dc.contributor.authorGeffen, Nathanen_ZA
dc.date.accessioned2014-11-11T12:58:36Z
dc.date.available2014-11-11T12:58:36Z
dc.date.issued1998en_ZA
dc.descriptionBibliography: leaves 112-121.en_ZA
dc.description.abstractThis thesis reports on the process of implementing pattern recognition systems using classification models such as artificial neural networks (ANNs) and algorithms whose theoretical foundations come from statistics. The issues involved in implementing several classification models and pre-processing operators - that are applied to patterns before classification takes place - are discussed and a methodology that is commonly used in developing pattern recognition systems is described. In addition, a number of pattern recognition systems for two image recognition problems that occur in the field of image matching have been developed. These image recognition problems and the issues involved in solving them are described in detail. Numerous experiments were carried out to test the accuracy and speed of the systems developed to solve these problems. These experiments and their results are also discussed.en_ZA
dc.identifier.apacitationGeffen, N. (1998). <i>Pattern recognition and the nondeterminable affine parameter problem</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Computer Science. Retrieved from http://hdl.handle.net/11427/9563en_ZA
dc.identifier.chicagocitationGeffen, Nathan. <i>"Pattern recognition and the nondeterminable affine parameter problem."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Computer Science, 1998. http://hdl.handle.net/11427/9563en_ZA
dc.identifier.citationGeffen, N. 1998. Pattern recognition and the nondeterminable affine parameter problem. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Geffen, Nathan AB - This thesis reports on the process of implementing pattern recognition systems using classification models such as artificial neural networks (ANNs) and algorithms whose theoretical foundations come from statistics. The issues involved in implementing several classification models and pre-processing operators - that are applied to patterns before classification takes place - are discussed and a methodology that is commonly used in developing pattern recognition systems is described. In addition, a number of pattern recognition systems for two image recognition problems that occur in the field of image matching have been developed. These image recognition problems and the issues involved in solving them are described in detail. Numerous experiments were carried out to test the accuracy and speed of the systems developed to solve these problems. These experiments and their results are also discussed. DA - 1998 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1998 T1 - Pattern recognition and the nondeterminable affine parameter problem TI - Pattern recognition and the nondeterminable affine parameter problem UR - http://hdl.handle.net/11427/9563 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/9563
dc.identifier.vancouvercitationGeffen N. Pattern recognition and the nondeterminable affine parameter problem. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Computer Science, 1998 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/9563en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Computer Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherComputer Scienceen_ZA
dc.titlePattern recognition and the nondeterminable affine parameter problemen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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