Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/77066
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DC FieldValueLanguage
dc.coverage.spatialComputer Science
dc.date.accessioned2016-03-21T09:55:01Z-
dc.date.available2016-03-21T09:55:01Z-
dc.identifier.urihttp://hdl.handle.net/10603/77066-
dc.description.abstractTo improve the quality of real time aerial river ice images using pre processing techniques To separate the different ice regions from enhanced images using pixel intensities To implement feature extraction techniques to obtain structured feature vectors using newlineseparated ice regions To propose hybrid algorithms for optimal feature subset selection to produce higher classification rate using computational intelligence technique To evaluate the performance of developed algorithms with noisy and denoised images
dc.format.extent226
dc.languageEnglish
dc.relationReferences / 127
dc.rightsuniversity
dc.titleOptimized Feature Subset Selection for Classification of River Ice Types from Aerial Images
dc.title.alternative
dc.creator.researcherBharathi P.T
dc.subject.keywordFeature extraction
dc.subject.keywordFeature selection
dc.subject.keywordRiver Ice images
dc.description.note
dc.contributor.guideSubashini P
dc.publisher.placeCoimbatore
dc.publisher.universityAvinashilingam Deemed University For Women
dc.publisher.institutionDepartment of Computer Science
dc.date.registered10/03/2011
dc.date.completed03/03/2015
dc.date.awarded14/03/2016
dc.format.dimensions210 x 290 mm
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science

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ptbharathi_chapter3.pdf1.12 MBAdobe PDFView/Open
ptbharathi_chapter4.pdf2.37 MBAdobe PDFView/Open
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ptbharathi_chapter6.pdf834.31 kBAdobe PDFView/Open
ptbharathi_chapter7.pdf6 MBAdobe PDFView/Open
ptbharathi_chapter8.pdf111.22 kBAdobe PDFView/Open
ptbharathi_chapter9.pdf213.55 kBAdobe PDFView/Open
ptbharathi_intro.pdf518.99 kBAdobe PDFView/Open


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