1. Shodhganga@INFLIBNET
  2. Koneru Lakshmaiah Education Foundation
  3. Department of Computer Science and Engineering
Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/300526
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DC FieldValueLanguage
dc.coverage.spatial
dc.date.accessioned2020-09-22T20:15:00Z-
dc.date.available2020-09-22T20:15:00Z-
dc.identifier.urihttp://hdl.handle.net/10603/300526-
dc.description.abstractnewline
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleDeveloping a defect detection model by using filter based feature selection and ensemble classification techniques for heterogeneous defect datasets
dc.title.alternative
dc.creator.researcherE Sridevi
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Software Engineering
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideY Prasanth
dc.publisher.placeVaddeswaram
dc.publisher.universityKoneru Lakshmaiah Education Foundation
dc.publisher.institutionDepartment of Computer Science and Engineering
dc.date.registered06/07/2013
dc.date.completed2020
dc.date.awarded12/06/2020
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science and Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File576.52 kBAdobe PDFView/Open
02_declaration.pdf434.59 kBAdobe PDFView/Open
03_certificate.pdf695.87 kBAdobe PDFView/Open
04_acknowle.pdf372.1 kBAdobe PDFView/Open
05_abtract.pdf354.49 kBAdobe PDFView/Open
06_tableofcontent.pdf739.74 kBAdobe PDFView/Open
07_list_of_table.pdf352.56 kBAdobe PDFView/Open
08_list_of_figure.pdf359.93 kBAdobe PDFView/Open
09_chapter1.pdf886.37 kBAdobe PDFView/Open
10_chapter2.pdf726.18 kBAdobe PDFView/Open
11_chapter3.pdf2.35 MBAdobe PDFView/Open
12_chapter4.pdf6.15 MBAdobe PDFView/Open
13_chapter5.pdf3.06 MBAdobe PDFView/Open
14_conclusion_summary.pdf370.7 kBAdobe PDFView/Open
15_bibolography.pdf1.21 MBAdobe PDFView/Open
80_recommendation.pdf14.09 MBAdobe PDFView/Open
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