Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/537756
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DC FieldValueLanguage
dc.coverage.spatialElectronics and Communication Engineeering
dc.date.accessioned2024-01-05T12:55:18Z-
dc.date.available2024-01-05T12:55:18Z-
dc.identifier.urihttp://hdl.handle.net/10603/537756-
dc.description.abstractAvailable
dc.format.extentxviii, 208
dc.languageEnglish
dc.relationno.of references 181
dc.rightsuniversity
dc.titleMachine learning approach for detection and classification of diabetic retinopathy through fundus eye images
dc.title.alternative-
dc.creator.researcherHardas, Minal Sudarshan
dc.subject.keywordDiabetic retinopathy
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.description.notereferences p. 195 - 208
dc.contributor.guideMathur, Sumit
dc.publisher.placeUdaipur
dc.publisher.universitySir Padampat Singhania University
dc.publisher.institutionDepartment of Electronics and Communication Engineering
dc.date.registered2019
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensions-
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Electronics and Communication Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File13.43 kBAdobe PDFView/Open
02_preliminary pages.pdf184.92 kBAdobe PDFView/Open
03_content.pdf18.98 kBAdobe PDFView/Open
04_abstract.pdf84.67 kBAdobe PDFView/Open
05_chapter 1.pdf1.05 MBAdobe PDFView/Open
06_chapter 2.pdf495.13 kBAdobe PDFView/Open
07_chapter 3.pdf2.53 MBAdobe PDFView/Open
08_chapter 4.pdf1.15 MBAdobe PDFView/Open
09_conclusion and future directions.pdf16.63 kBAdobe PDFView/Open
10_annexure.pdf1.96 MBAdobe PDFView/Open
80_recommendation.pdf29.1 kBAdobe PDFView/Open


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