Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/581517
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dc.coverage.spatial
dc.date.accessioned2024-08-07T12:08:28Z-
dc.date.available2024-08-07T12:08:28Z-
dc.identifier.urihttp://hdl.handle.net/10603/581517-
dc.description.abstractDiabetic Retinopathy is a diabetes complication which occurs in human eyes newlineand affects the human vision. The damage which occurs in human eye is due to the blood newlinevessels of the light-sensitive tissues at the back portion of the eyes. To identify diabetic newlineRetinopathy, there are some effects which occur in one s human eyes, such as spots or newlinedark strings floating in vision, blurred vision, fluctuating vision, dark and empty areas in newlinevision, vision loss and blindness. There are few types of DR occurs normally which is newlineidentified in 4 stages such as newline1. Mild -Non proliferative DR newline2. Moderate-Non Proliferative DR newline3. Severe Non-Proliferative DR newline4. Proliferative DR newlineTo identify and analyze the effects of DR, there are benchmarked literature newlineavailable with extensive amount of research which dwells into the detection and newlineclassification of DR. when we have done a thorough literature, we pinpointed few newlineresearch challenges, which include red lesion detection, associated to time complexity, newlineperfect classification algorithms and also the design of auto adjusted convex lens to detect newlineand classify DR at a prior stage is the paramount issue newline
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleRetilenz Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
dc.title.alternative
dc.creator.researcherVanusha, D
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Theory and Methods
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideAmutha, B
dc.publisher.placeKattankulathur
dc.publisher.universitySRM Institute of Science and Technology
dc.publisher.institutionDepartment of Computer Science Engineering
dc.date.registered
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science Engineering

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01_title page.pdfAttached File281.54 kBAdobe PDFView/Open
02_preliminary page.pdf433.7 kBAdobe PDFView/Open
03_content.pdf471.12 kBAdobe PDFView/Open
04_abstract.pdf282.73 kBAdobe PDFView/Open
05_chapter 1.pdf1.27 MBAdobe PDFView/Open
06_chapter 2.pdf1.02 MBAdobe PDFView/Open
07_chapter 3.pdf1.21 MBAdobe PDFView/Open
08_chapter 4.pdf726.11 kBAdobe PDFView/Open
09_chapter 5.pdf749.74 kBAdobe PDFView/Open
10_chapter 6.pdf749.9 kBAdobe PDFView/Open
11_chapter 7.pdf676.27 kBAdobe PDFView/Open
12_chapter 8.pdf270.53 kBAdobe PDFView/Open
13_annexures.pdf1.8 MBAdobe PDFView/Open
80_recommendation.pdf418.6 kBAdobe PDFView/Open


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