Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/577491
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dc.coverage.spatial
dc.date.accessioned2024-07-19T10:19:06Z-
dc.date.available2024-07-19T10:19:06Z-
dc.identifier.urihttp://hdl.handle.net/10603/577491-
dc.description.abstractFile Attached newline
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleAn early diagnosis of blastocyst quality and endometrium receptivity using deep learning framework with modified whale optimisation technique
dc.title.alternative
dc.creator.researcherSatya Kiranmai, Tadepalli
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Software Engineering
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideLakshmi, P V
dc.publisher.placeVisakhapatnam
dc.publisher.universityGITAM University
dc.publisher.institutionDepartment of Computer Science and Engineering
dc.date.registered
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science and Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdf.pdfAttached File62.59 kBAdobe PDFView/Open
02_prelim pages.pdf.pdf53.06 kBAdobe PDFView/Open
03_contents.pdf.pdf36.34 kBAdobe PDFView/Open
04_abstract.pdf.pdf6.51 kBAdobe PDFView/Open
05_chapter 1.pdf.pdf183.45 kBAdobe PDFView/Open
06_chapter 2.pdf.pdf232.04 kBAdobe PDFView/Open
07_chapter 3.pdf.pdf385.74 kBAdobe PDFView/Open
08_chapter 4.pdf.pdf591.37 kBAdobe PDFView/Open
09_chapter 5.pdf.pdf636.21 kBAdobe PDFView/Open
10_chapter 6.pdf.pdf352.94 kBAdobe PDFView/Open
11_chapter 7.pdf.pdf85.1 kBAdobe PDFView/Open
12_annexures.pdf.pdf199.51 kBAdobe PDFView/Open
80_recommendation.pdf146.67 kBAdobe PDFView/Open


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