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The Cryosphere An interactive open-access journal of the European Geosciences Union
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TC | Articles | Volume 14, issue 11
The Cryosphere, 14, 3687–3705, 2020
https://doi.org/10.5194/tc-14-3687-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
The Cryosphere, 14, 3687–3705, 2020
https://doi.org/10.5194/tc-14-3687-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 05 Nov 2020

Research article | 05 Nov 2020

DeepBedMap: a deep neural network for resolving the bed topography of Antarctica

Wei Ji Leong and Huw Joseph Horgan

Data sets

DeepBedMap Digital Elevation Model W. J. Leong and H. J. Horgan https://doi.org/10.5281/zenodo.3752613

Using a deep neural network to better resolve the bed topography of Antarctica Wei Ji Leong and Huw Joseph Horgan https://doi.org/10.17605/OSF.IO/96APW

Model code and software

DeepBedMap neural network model W. J. Leong and H. J. Horgan https://doi.org/10.5281/zenodo.3752613

Publications Copernicus
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Short summary
A machine learning technique similar to the one used to enhance everyday photographs is applied to the problem of getting a better picture of Antarctica's bed – the part which is hidden beneath the ice. By taking hints from what satellites can observe at the ice surface, the novel method learns to generate a rougher bed topography that complements existing approaches, with a result that is able to be used by scientists running fine-scale ice sheet models relevant to predicting future sea levels.
A machine learning technique similar to the one used to enhance everyday photographs is applied...
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