Out-of-the-box Calving Front Detection Method Using Deep Learning

Herrmann O, Gourmelon N, Seehaus T, Maier A, Fürst J, Braun M, Christlein V (2023)

Publication Status: Accepted

Publication Type: Journal article, Original article

Future Publication Type: Journal article

Publication year: 2023

Journal

Cryosphere European Geosciences Union (EGU) / Copernicus Publications

Book Volume: 17

Pages Range: 4957–4977

DOI: 10.5194/tc-17-4957-2023

Authors with CRIS profile

Oskar Herrmann Institut für Geographie Nora Gourmelon Lehrstuhl für Informatik 5 (Mustererkennung) Thorsten Seehaus Institut für Geographie Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung) Johannes Fürst Institut für Geographie Matthias Braun Professur für Geographie (Fernerkundung und GIS) Vincent Christlein Lehrstuhl für Informatik 5 (Mustererkennung)

Related research project(s)

International Doctoral Program: Measuring and Modelling Mountain glaciers and ice caps in a Changing Climate (M³OCCA) (MOCCA) June 1, 2022 - May 31, 2026 Mass balance and Ice Dynamics of Antarctic Peninsula glaciers (MIT-AP) May 2, 2020 - Dec. 31, 2022 Tapping the potential of Earth Observations (TAPE) April 1, 2019 - March 31, 2022

How to cite

APA:

Herrmann, O., Gourmelon, N., Seehaus, T., Maier, A., Fürst, J., Braun, M., & Christlein, V. (2023). Out-of-the-box Calving Front Detection Method Using Deep Learning. Cryosphere, 17, 4957–4977. https://doi.org/10.5194/tc-17-4957-2023

MLA:

Herrmann, Oskar, et al. "Out-of-the-box Calving Front Detection Method Using Deep Learning." Cryosphere 17 (2023): 4957–4977.

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