Master Thesis Online
Deep Learning in ArcGIS Pro using Lidar data for automatic detection of archaeological structures
Baudhuin, Alice 
Promotor(s) :
Kokalj, Ziga
;
Jonard, François
Date of defense : 29-Jun-2023/30-Jun-2023 • Permalink : http://hdl.handle.net/2268.2/17638
master_thesis.pdfDetails
| Title : | Deep Learning in ArcGIS Pro using Lidar data for automatic detection of archaeological structures |
| Translated title : | [fr] Deep Learning dans ArcGIS Pro sur base de données Lidar pour la détection automatique de structures archéologiques |
| Author : | Baudhuin, Alice
|
| Date of defense : | 29-Jun-2023/30-Jun-2023 |
| Advisor(s) : | Kokalj, Ziga
Jonard, François
|
| Committee's member(s) : | Nascetti, Andrea
Hallot, Pierre
|
| Language : | English |
| Number of pages : | 97 |
| Keywords : | [en] Deep learning, lidar, archaeology |
| Discipline(s) : | Physical, chemical, mathematical & earth Sciences > Space science, astronomy & astrophysics |
| Research unit : | Institute of Anthropological and Spatial Studies |
| Target public : | Researchers Professionals of domain Student General public |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en sciences spatiales, à finalité spécialisée |
| Faculty: | Master thesis of the Faculté des Sciences |
Abstract
[en] This Master Thesis studies the application of deep learning to lidar data for archaeological purposes. Specific lidar-derived visualisations, which are especially relevant in the case of archaeology, are used. The goal is to investigate several deep learning models using the ArcGIS Pro software, and determine their performance in finding new archaeological features when applied to these visualisations.
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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.