Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/568159
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2024-05-30T13:27:55Z | - |
dc.date.available | 2024-05-30T13:27:55Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/568159 | - |
dc.description.abstract | newline | |
dc.format.extent | xvii, 313 p | |
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Deep Convolution Neural Network Based Liver Cancer Detection | |
dc.title.alternative | ||
dc.creator.researcher | Napte, Kiran Malhari | |
dc.subject.keyword | Automatic Liver Cancer Detection | |
dc.subject.keyword | Computed Tomography | |
dc.subject.keyword | Deep Learning | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering Multidisciplinary | |
dc.subject.keyword | Liver Segmentation | |
dc.subject.keyword | Medical Image Enhancement | |
dc.description.note | ||
dc.contributor.guide | Mahajan, Aurag | |
dc.publisher.place | Pune | |
dc.publisher.university | Symbiosis International University | |
dc.publisher.institution | Faculty of Engineering | |
dc.date.registered | 2019 | |
dc.date.completed | 2024 | |
dc.date.awarded | 2024 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 483.95 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.88 MB | Adobe PDF | View/Open | |
03_chapter 1..pdf | 593.28 kB | Adobe PDF | View/Open | |
04_chapter 2..pdf | 330.88 kB | Adobe PDF | View/Open | |
05_chapter 3..pdf | 813.1 kB | Adobe PDF | View/Open | |
06_chapter 4..pdf | 1.33 MB | Adobe PDF | View/Open | |
07_chapter 5..pdf | 1.95 MB | Adobe PDF | View/Open | |
08_chapter 6..pdf | 35.01 kB | Adobe PDF | View/Open | |
10_annexure..pdf | 6.09 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 514.77 kB | Adobe PDF | View/Open |
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