Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/597954
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dc.coverage.spatial
dc.date.accessioned2024-10-25T12:13:23Z-
dc.date.available2024-10-25T12:13:23Z-
dc.identifier.urihttp://hdl.handle.net/10603/597954-
dc.description.abstractnewline
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleAnalysis and Implementation of Nature Inspired Deep Learning Techniques for Efficient Tomato Plant Leaf Disease Detection and Classification
dc.title.alternative
dc.creator.researcherE Gangadevi
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Artificial Intelligence
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideShobarani R
dc.publisher.placeChennai
dc.publisher.universityDr. M.G.R. Educational and Research Institute
dc.publisher.institutionDepartment of Computer Science
dc.date.registered2019
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions
dc.format.accompanyingmaterialCD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science

Files in This Item:
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10-chapter 6.pdfAttached File123.41 kBAdobe PDFView/Open
11-annexures.pdf424.18 kBAdobe PDFView/Open
1-titlepage.pdf139.16 kBAdobe PDFView/Open
2 - preliminary pages.pdf292.51 kBAdobe PDFView/Open
3- table of contents.pdf153.68 kBAdobe PDFView/Open
4- abstract.pdf106.66 kBAdobe PDFView/Open
5-chapter 1.pdf796.67 kBAdobe PDFView/Open
6-chapter 2.pdf405.04 kBAdobe PDFView/Open
7-chapter 3.pdf1.34 MBAdobe PDFView/Open
80_recommendation.pdf252.23 kBAdobe PDFView/Open
8-chapter 4.pdf2.01 MBAdobe PDFView/Open
9-chapter 5.pdf461.54 kBAdobe PDFView/Open


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