Source identification of captured video using photo response non-uniformity noise pattern and svm classifiers
Also available in printed version
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | |
| التنسيق: | Master's thesis |
| منشور في: |
Universiti Teknologi Malaysia
2025
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://utmik.utm.my/handle/123456789/100950 |
| Abstract | Abstract here |
| _version_ | 1854975054137262080 |
|---|---|
| author | Roya Esmaeilani |
| author2 | Ghazali Sulong, supervisor |
| author_facet | Ghazali Sulong, supervisor Roya Esmaeilani |
| author_sort | Roya Esmaeilani |
| description | Also available in printed version |
| format | Master's thesis |
| id | utm-123456789-100950 |
| institution | Universiti Teknologi Malaysia |
| publishDate | 2025 |
| publisher | Universiti Teknologi Malaysia |
| record_format | dspace |
| record_pdf | Abstract |
| spelling | utm-123456789-1009502025-08-20T20:00:31Z Source identification of captured video using photo response non-uniformity noise pattern and svm classifiers Roya Esmaeilani Ghazali Sulong, supervisor Computer science and information system Also available in printed version Urbanization and increase in population are due to many factors particularly the economic and political stabilities. The direct impact of the phenomena is the increase in the demand for water especially for drinking water. With regard to the demand for drinking water, there is a serious need for effective maintenance of water assets so that the assets life cycle may be maximized. Directly related to the maintenance is the assets inventory because water company may monitor the assets in order to provide excellent and effective service. Effective planning system for water assets is needed in order to fullfill the increasing demand for drinking water. The purpose of this study is to investigate on the use of GIS in water asset planning with a particular focus on aspect of the water asset inventory and maintenance. How GIS technology provides advantages in water asset planning? The objectives of this study to (i) review the concept of water asset management, (ii) develop a database of water asset in the study, and (iii) use GIS functionalities for the planning and inventory of water asset management. A new residential area, Setia Eco Garden located within Mukim Pulai, in Johor Bahru district was chosen as the study area. Results showed that GIS can help water companies in inventory and maintenance management of water assets and GIS is a very useful tool in managing water assets fahmimoksen UTM 96 p. Thesis (Sarjana Sains (Sains Komputer)) - Universiti Teknologi Malaysia, 2014 2025-04-10T04:26:26Z 2025-04-10T04:26:26Z 2014 Master's thesis https://utmik.utm.my/handle/123456789/100950 valet-20160420-120042 vital:86446 Closed Access UTM Complete Unpublished application/pdf Universiti Teknologi Malaysia |
| spellingShingle | Computer science and information system Roya Esmaeilani Source identification of captured video using photo response non-uniformity noise pattern and svm classifiers |
| thesis_level | Master |
| title | Source identification of captured video using photo response non-uniformity noise pattern and svm classifiers |
| title_full | Source identification of captured video using photo response non-uniformity noise pattern and svm classifiers |
| title_fullStr | Source identification of captured video using photo response non-uniformity noise pattern and svm classifiers |
| title_full_unstemmed | Source identification of captured video using photo response non-uniformity noise pattern and svm classifiers |
| title_short | Source identification of captured video using photo response non-uniformity noise pattern and svm classifiers |
| title_sort | source identification of captured video using photo response non uniformity noise pattern and svm classifiers |
| topic | Computer science and information system |
| url | https://utmik.utm.my/handle/123456789/100950 |
| work_keys_str_mv | AT royaesmaeilani sourceidentificationofcapturedvideousingphotoresponsenonuniformitynoisepatternandsvmclassifiers |