Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/180800
Title: | Abnor mality detection in ultrasound kidney images using machine learning techniques |
Researcher: | Baby, Christina |
Guide(s): | Parthiban, Latha |
Keywords: | Abnor mality machine techniques |
University: | St. Peters University |
Completed Date: | 2016 |
Abstract: | Available Abstract |
Pagination: | n.d. |
URI: | http://hdl.handle.net/10603/180800 |
Appears in Departments: | Department Of Electrical and Electronics Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 21.75 kB | Adobe PDF | View/Open |
02_certificate.pdf | 7.1 kB | Adobe PDF | View/Open | |
03_declaration.pdf | 6.96 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 8.51 kB | Adobe PDF | View/Open | |
05_abstract.pdf | 10.04 kB | Adobe PDF | View/Open | |
06_contents.pdf | 37.52 kB | Adobe PDF | View/Open | |
07_chapter 1.pdf | 286.02 kB | Adobe PDF | View/Open | |
08_chapter 2.pdf | 527.17 kB | Adobe PDF | View/Open | |
09_chapter 3.pdf | 422.79 kB | Adobe PDF | View/Open | |
10_chapter 4.pdf | 124.49 kB | Adobe PDF | View/Open | |
11_chapter 5.pdf | 313.03 kB | Adobe PDF | View/Open | |
12_chapter 6.pdf | 287.43 kB | Adobe PDF | View/Open | |
13_chapter 7.pdf | 18.28 kB | Adobe PDF | View/Open | |
14_reference.pdf | 78.7 kB | Adobe PDF | View/Open |
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