Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/570318
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DC FieldValueLanguage
dc.coverage.spatial
dc.date.accessioned2024-06-10T11:21:49Z-
dc.date.available2024-06-10T11:21:49Z-
dc.identifier.urihttp://hdl.handle.net/10603/570318-
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleEfficient Lung Tumor Segmentation and Classification Using Hybridized Deep Ensemble Model
dc.title.alternative
dc.creator.researcherMonita Wahengbam
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Artificial Intelligence
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideKhanna, V
dc.publisher.placeChennai
dc.publisher.universityBharath Institute of Higher Education and Research
dc.publisher.institutionDepartment of Engineering and Technology(Computer Science and 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 and Engineering

Files in This Item:
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01_title.pdfAttached File173.83 kBAdobe PDFView/Open
02_prelim pages.pdf558.17 kBAdobe PDFView/Open
03_content.pdf170.89 kBAdobe PDFView/Open
04_abstract.pdf126.82 kBAdobe PDFView/Open
05_chapter 1.pdf1.99 MBAdobe PDFView/Open
06_chapter 2.pdf2 MBAdobe PDFView/Open
07_chapter 3.pdf1.99 MBAdobe PDFView/Open
08_chapter 4.pdf1.99 MBAdobe PDFView/Open
09_chapter 5.pdf1.99 MBAdobe PDFView/Open
10_chapter 6.pdf1.99 MBAdobe PDFView/Open
11_chapter 7.pdf1.99 MBAdobe PDFView/Open
12_chapter 8.pdf1.99 MBAdobe PDFView/Open
13_annexures.pdf1.99 MBAdobe PDFView/Open
80_recommendation.pdf355.88 kBAdobe PDFView/Open


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