Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/507794
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DC FieldValueLanguage
dc.coverage.spatialElectronics and Communication
dc.date.accessioned2023-08-18T09:51:48Z-
dc.date.available2023-08-18T09:51:48Z-
dc.identifier.urihttp://hdl.handle.net/10603/507794-
dc.format.extent-
dc.languageEnglish
dc.relationNo of References 83
dc.rightsuniversity
dc.titleIntegrated framework for pose estimation using artificial intelligent techniques
dc.title.alternative
dc.creator.researcherPatel, Manisha C.
dc.subject.keyword2D Pose
dc.subject.keywordConvolutional Neural Networks
dc.subject.keywordDeep Learning
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.subject.keywordMachine Learning
dc.subject.keywordOptimization Algorithms
dc.subject.keywordPersonal Exercise Assistance
dc.subject.keywordPose Estimation
dc.description.noteReferences p. 117-123
dc.contributor.guideKalani, N. B.
dc.publisher.placeRajkot
dc.publisher.universityRK University
dc.publisher.institutionFaculty of Technology
dc.date.registered2020
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensions-
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Technology

Files in This Item:
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01_title page.pdfAttached File134.66 kBAdobe PDFView/Open
02 preliminary page.pdf23.72 MBAdobe PDFView/Open
03_content.pdf278.89 kBAdobe PDFView/Open
04_abstract and graphical abstract.pdf217.19 kBAdobe PDFView/Open
05_chapter 1.pdf457.76 kBAdobe PDFView/Open
06_chapter 2.pdf1.04 MBAdobe PDFView/Open
07_chapter 3.pdf197.99 kBAdobe PDFView/Open
08_chapter 4.pdf963.98 kBAdobe PDFView/Open
09_chapter 5.pdf1.11 MBAdobe PDFView/Open
10_chapter 6.pdf195.39 kBAdobe PDFView/Open
11_chapter 7.pdf121.45 kBAdobe PDFView/Open
12_annexures.pdf229.92 kBAdobe PDFView/Open
80_recommendation.pdf250.62 kBAdobe PDFView/Open


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