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The Cryosphere An interactive open-access journal of the European Geosciences Union
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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.
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TC | Articles | Volume 14, issue 11
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.
TC | Articles | Volume 14, issue 11

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

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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.
Read more
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The Cryosphere

An interactive open-access journal of the European Geosciences Union

All site content, except where otherwise noted, is licensed under the Creative Commons Attribution 4.0 License.
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