Conditional Random Fields for Improving Deep Learning-based Glacier Calving Front Delineations
Gourmelon N, Klink J, Seehaus T, Braun M, Maier A, Christlein V (2023)
Publication Language: English
Publication Status: Accepted
Publication Type: Conference contribution, Conference Contribution
Future Publication Type: Conference contribution
Publication year: 2023
Pages Range: 4939-4942
Conference Proceedings Title: IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Event location: Pasadena, California
URI: https://ieeexplore.ieee.org/document/10282915
DOI: 10.1109/IGARSS52108.2023.10282915
Authors with CRIS profile
Nora Gourmelon
Lehrstuhl für Informatik 5 (Mustererkennung)
Julian Klink
Lehrstuhl für Informatik 5 (Mustererkennung)
Thorsten Seehaus
Institut für Geographie
Matthias Braun
Professur für Geographie (Fernerkundung und GIS)
Andreas Maier
Lehrstuhl für Informatik 5 (Mustererkennung)
Vincent Christlein
Lehrstuhl für Informatik 5 (Mustererkennung)
Related research project(s)
How to cite
APA:
Gourmelon, N., Klink, J., Seehaus, T., Braun, M., Maier, A., & Christlein, V. (2023). Conditional Random Fields for Improving Deep Learning-based Glacier Calving Front Delineations. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 4939-4942). Pasadena, California, US.
MLA:
Gourmelon, Nora, et al. "Conditional Random Fields for Improving Deep Learning-based Glacier Calving Front Delineations." Proceedings of the International Geoscience and Remote Sensing Symposium 2023, Pasadena, California 2023. 4939-4942.
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