Master Thesis Online
Machine learning for image-based wavefront sensing
Vanberg, Pierre-Olivier 
Promotor(s) :
Absil, Olivier
;
Louppe, Gilles
Date of defense : 26-Jun-2019/27-Jun-2019 • Permalink : http://hdl.handle.net/2268.2/6800
All files (archive ZIP)
pvanberg_thesis.pdfDetails
| Title : | Machine learning for image-based wavefront sensing |
| Author : | Vanberg, Pierre-Olivier
|
| Date of defense : | 26-Jun-2019/27-Jun-2019 |
| Advisor(s) : | Absil, Olivier
Louppe, Gilles
|
| Committee's member(s) : | Orban De Xivry, Gilles
Van Droogenbroeck, Marc
|
| Language : | English |
| Discipline(s) : | Engineering, computing & technology > Computer science |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en ingénieur civil physicien, à finalité approfondie |
| Faculty: | Master thesis of the Faculté des Sciences appliquées |
Abstract
[en] Astronomical images are often degraded by the disturbance of the Earth’s atmosphere. This thesis proposes to improve image-based wavefront sensing techniques using machine learning algorithms. Deep convolutional neural networks (CNN) have thus been trained to estimate the wavefront using one or multiple intensity measurements.
File(s)
Document(s)
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.