1. Shodhganga@INFLIBNET
  2. Sri Padmavathi Womens University
  3. Department of Computer Science
Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/465073
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DC FieldValueLanguage
dc.coverage.spatialcomputer science
dc.date.accessioned2023-02-20T12:27:29Z-
dc.date.available2023-02-20T12:27:29Z-
dc.identifier.urihttp://hdl.handle.net/10603/465073-
dc.description.abstractnewline
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleFeature Extraction and Classification of Ultrasound Images for Polycystic Ovary Syndrome Detection using Deep learning techniques
dc.title.alternative
dc.creator.researcherVasavi,G
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Artificial Intelligence
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideJyothi, S
dc.publisher.placeTirupati
dc.publisher.universitySri Padmavathi Womens University
dc.publisher.institutionDepartment of Computer Science
dc.date.registered2014
dc.date.completed2021
dc.date.awarded2021
dc.format.dimensions35
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science

Files in This Item:
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011_chpater 6.pdfAttached File193.18 kBAdobe PDFView/Open
01_title .pdf759.14 kBAdobe PDFView/Open
02_prelimnary.pdf1.82 MBAdobe PDFView/Open
03_content .pdf296.09 kBAdobe PDFView/Open
04_abstract .pdf279.62 kBAdobe PDFView/Open
05_chapter 1.pdf267.83 kBAdobe PDFView/Open
06_chpater 2.pdf714.13 kBAdobe PDFView/Open
07_chapter 3.pdf1.75 MBAdobe PDFView/Open
08_chapter 4.pdf1.77 MBAdobe PDFView/Open
09_chpater 5.pdf1.95 MBAdobe PDFView/Open
10_annexure.pdf548.69 kBAdobe PDFView/Open
80_recommendation.pdf948.79 kBAdobe PDFView/Open
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