Master Thesis Online
Automatic OilSpill detection and monitoring with supervised machine learning and SAR remote sensing
Stock, Damien 
Promotor(s) :
Defrere, Denis
;
Van Droogenbroeck, Marc
Date of defense : 7-Sep-2020/8-Sep-2020 • Permalink : http://hdl.handle.net/2268.2/9940
Details
| Title : | Automatic OilSpill detection and monitoring with supervised machine learning and SAR remote sensing |
| Author : | Stock, Damien
|
| Date of defense : | 7-Sep-2020/8-Sep-2020 |
| Advisor(s) : | Defrere, Denis
Van Droogenbroeck, Marc
|
| Committee's member(s) : | Kirkove, Murielle
Marée, Raphaël
Orban, Anne
|
| Language : | English |
| Number of pages : | 96 |
| Keywords : | [en] Oil spill detection SAR Convolutional neural network |
| Discipline(s) : | Physical, chemical, mathematical & earth Sciences > Space science, astronomy & astrophysics |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en sciences spatiales, à finalité approfondie |
| Faculty: | Master thesis of the Faculté des Sciences |
Abstract
[en] This master thesis had as aim the analysis of the possibility of making an oil spill detection automation tool based on SAR images and convolutional neural network.
File(s)
Document(s)
Oil_Spill_Detection.pdf
Description: Stock Damien
Size: 23.28 MB
Format: Adobe PDF
Cite this master thesis
All documents available on MatheO are protected by copyright and subject to the usual rules for fair use.
The University of Liège does not guarantee the scientific quality of these students' works or the accuracy of all the information they contain.
The University of Liège does not guarantee the scientific quality of these students' works or the accuracy of all the information they contain.