Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/435053
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DC FieldValueLanguage
dc.coverage.spatial
dc.date.accessioned2023-01-02T13:04:53Z-
dc.date.available2023-01-02T13:04:53Z-
dc.identifier.urihttp://hdl.handle.net/10603/435053-
dc.description.abstractnewline
dc.format.extentxv, 132 p.
dc.languageEnglish
dc.relation114
dc.rightsuniversity
dc.titleEnhanced convolutional neural network architectures by hyper parameter tuning for effective classification of diabetic retinopathy stages
dc.title.alternative
dc.creator.researcherYazhini, K
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Software Engineering
dc.subject.keywordDeep Learning
dc.subject.keywordDiabetic diagnosis models
dc.subject.keywordConvolutional Neural Network
dc.description.note
dc.contributor.guideLoganathan, D
dc.publisher.placePondicherry
dc.publisher.universityPondicherry University
dc.publisher.institutionPondicherry Engineering College
dc.date.registered
dc.date.completed2021
dc.date.awarded2021
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Pondicherry Engineering College

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File119.63 kBAdobe PDFView/Open
02_prelim pages.pdf370.32 kBAdobe PDFView/Open
03_content.pdf27.09 kBAdobe PDFView/Open
04_abstract.pdf11.54 kBAdobe PDFView/Open
05_chapter 1.pdf546.17 kBAdobe PDFView/Open
06_chapter 2.pdf292.55 kBAdobe PDFView/Open
07_chapter 3.pdf89.94 kBAdobe PDFView/Open
08_chapter 4.pdf455.88 kBAdobe PDFView/Open
09_chapter 5.pdf1.03 MBAdobe PDFView/Open
10_chapter 6.pdf734.78 kBAdobe PDFView/Open
11_chapter 7.pdf714.75 kBAdobe PDFView/Open
12_chapter 8.pdf13.62 kBAdobe PDFView/Open
13_annexures.pdf193.16 kBAdobe PDFView/Open
80_recommendation.pdf128.51 kBAdobe PDFView/Open


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