Master Thesis Online
Machine learning for image-based wavefront sensing
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pvanberg_thesis.pdf
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
Details
| 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.
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Cite this master thesis
APA
Vanberg, P.-O. (2019). Machine learning for image-based wavefront sensing. (Unpublished master's thesis). Université de Liège, Liège, Belgique. Retrieved from https://matheo.uliege.be/handle/2268.2/6800
Chicago
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The University of Liège does not guarantee the scientific quality of these students' works or the accuracy of all the information they contain.