Nora Gourmelon
Nora Gourmelon, M. Sc.
- Since 11/2020:
Ph.D. Student at Pattern Recognition Lab, FAU Erlangen-Nürnberg - 10/2018 – 11/2020:
M. Sc. Computer Science, FAU Erlangen-Nürnberg - 08/2019 – 12/2019:
Semester abroad at Norges teknisk-naturvitenskapelige universitet in Trondheim, Norway - 10/2014 – 09/2019:
B. Sc. Computer Science, FAU Erlangen-Nürnberg - 09/2016 – 12/2016:
Semester abroad at Saint Mary`s University in Halifax, Canada
2019
-
Tapping the potential of Earth Observations
(FAU Funds)
Term: April 1, 2019 - March 31, 2022Ziel des Projekts ist es, die Zeitreihen von
Erdbeobachtungs(EO)-Daten mit innovativen Methoden des „Deep Learnings“
zu analysieren, um effiziente Algorithmen zur Bewältigung der großen
Datenmengen zu entwickeln. Der Wert dieser EO-Produkte wird durch
fortgeschrittene Interpolationstechniken und Assimilation in
geophysikalische Modelle, die es in der angewandten Mathematik gibt,
weiter erhöht.
2022
Conference Contributions
Dissecting Glaciers - Can an Automated Bio-Medical Image Segmentation Tool also Segment Glaciers?
EGU General Assembly 2022 (Vienna, Austria, May 23, 2022 - May 27, 2022)
DOI: 10.5194/egusphere-egu22-2726
BibTeX: Download
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2021
Journal Articles
Implications of Experiment Set-Ups for Residential Water End-Use Classification
In: Water 13 (2021), Article No.: 236
ISSN: 2073-4441
DOI: 10.3390/w13020236
URL: https://www.mdpi.com/2073-4441/13/2/236
BibTeX: Download
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Conference Contributions
Tapping the Potential of Earth Observation - Calving Front Detection in SAR Images using Deep Learning Techniques
EGU General Assembly 2021 (, April 19, 2021 - May 30, 2021)
DOI: 10.5194/egusphere-egu21-11280
BibTeX: Download
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2020
Conference Contributions
Implications of Experiment Set-Ups for Residential Water End-Use Classification
5th International Electronic Conference on Water Sciences (, November 16, 2020 - November 30, 2020)
DOI: 10.3390/ECWS-5-08225
URL: https://sciforum.net/paper/view/conference/8225
BibTeX: Download
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- 2022:
“The Birds” and “Calving Fronts and Where to Find Them”, Invited Talk at the Green AI Seminar, FAU, 5. Mai - 2021:
“Gletscherfronten und wo sie zu finden sind”, Fachsymposium “Artificial Intelligence for Life”, Hochschule für angewandte Wissenschaften Weihenstephan-Triesdorf, 22. Oktober - 2021:
“Glacier Fronts and Where to Find Them”, Pattern Recognition Symposium Summer 2021, 22. Juli - 2021:
“Application Area Water (in Different Physical States)”, Pattern Recognition Symposium Winter 2020/21, 18. February
- 2022:
“The Birds”, Pattern Recognition Symposium Winter 2021/22, 09. March - 2021:
“Calving Front Detection in SAR Images using Deep Learning Techniques”, #GeoWoche2021, Arbeitskreis Fernerkundung, 08. Oktober, link to abstract, link to poster
- 2022:
Best Poster Award at the Pattern Recognition Symposium Winter 2021/22 for the poster “The Birds” - 2021:
Prize for excellent Master’s thesis “End-use Classification Using High-Resolution Smart Water Meter Data” - 2020:
Best Paper Award at the 5th International Electronic Conference on Water Sciences in the Session “Water Resources Management and the Ecosphere Resilience and Adaptation”
Praktikum (PR)
Übung (UE)
-
Medizintechnik II Tutorenbesprechung
-
Medizintechnik II Tafelübung
This course will be held in person. Please note that the first meeting will be on Friday 29.4.
Type | Title | Status |
---|---|---|
Project | Evaluation of an Attention U-Net for Glacier Segmentation | running |
Project | Evaluation of an Optimized U-Net for Glacier Segmentation | running |
Project | Evaluation of a Bayesian U-Net for Glacier Segmentation | running |
MA thesis | Design and Evaluation of Machine Learning Applications for Space Systems | running |
MA thesis | Multi-Task Learning for Glacier Segmentation and Calving Front Detection with the nnU-Net Framework | finished |
Project | Temporal Information in Glacier Front Segmentation Using a 3D Conditional Random Field | finished |
Project | Evaluation of Different Loss Functions for Highly Unbalanced Segmentation | finished |
MA thesis | Incorporating Time Series Information into Glacier Segmentation and Front Detection using U-Nets in Combination with LSTMs and Multi-Task Learning | finished |
MA thesis | Image Segmentation via Transformers | finished |