DeepBedMap: A super-resolution neural network created bed topography of Antarctica

Going beyond BEDMAP2 using a super resolution deep neural network. deepbedmap_v1.1.0.zip: Python code for the DeepBedMap Super-Resolution Generative Adversarial Network. deepbedmap_dem.tif: Digital Elevation Model (250 m spatial resolution) in GeoTiff format, using Antarctic Polar Stereographic Proj...

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Bibliographic Details
Main Authors: Leong, Wei Ji, Horgan, Huw Joseph
Format: Dataset
Language:English
Published: Zenodo 2020
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.3752613
https://zenodo.org/record/3752613
id ftdatacite:10.5281/zenodo.3752613
record_format openpolar
spelling ftdatacite:10.5281/zenodo.3752613 2023-05-15T13:53:29+02:00 DeepBedMap: A super-resolution neural network created bed topography of Antarctica Leong, Wei Ji Horgan, Huw Joseph 2020 https://dx.doi.org/10.5281/zenodo.3752613 https://zenodo.org/record/3752613 en eng Zenodo https://dx.doi.org/10.5194/tc-14-3687-2020 https://dx.doi.org/10.5281/zenodo.3752614 https://dx.doi.org/10.5281/zenodo.4054246 Open Access GNU Lesser General Public License v3.0 or later https://www.gnu.org/licenses/lgpl-3.0-standalone.html lgpl-3.0+ info:eu-repo/semantics/openAccess Antarctica Digital Elevation Model Super-resolution Neural Network dataset Dataset 2020 ftdatacite https://doi.org/10.5281/zenodo.3752613 https://doi.org/10.5194/tc-14-3687-2020 https://doi.org/10.5281/zenodo.3752614 https://doi.org/10.5281/zenodo.4054246 2021-11-05T12:55:41Z Going beyond BEDMAP2 using a super resolution deep neural network. deepbedmap_v1.1.0.zip: Python code for the DeepBedMap Super-Resolution Generative Adversarial Network. deepbedmap_dem.tif: Digital Elevation Model (250 m spatial resolution) in GeoTiff format, using Antarctic Polar Stereographic Projection (EPSG:3031). srgan_generator_model_weights.npz: The Generator neural network weights/parameters as a NumPy zip file. Dataset Antarc* Antarctic Antarctica DataCite Metadata Store (German National Library of Science and Technology) Antarctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Antarctica
Digital Elevation Model
Super-resolution
Neural Network
spellingShingle Antarctica
Digital Elevation Model
Super-resolution
Neural Network
Leong, Wei Ji
Horgan, Huw Joseph
DeepBedMap: A super-resolution neural network created bed topography of Antarctica
topic_facet Antarctica
Digital Elevation Model
Super-resolution
Neural Network
description Going beyond BEDMAP2 using a super resolution deep neural network. deepbedmap_v1.1.0.zip: Python code for the DeepBedMap Super-Resolution Generative Adversarial Network. deepbedmap_dem.tif: Digital Elevation Model (250 m spatial resolution) in GeoTiff format, using Antarctic Polar Stereographic Projection (EPSG:3031). srgan_generator_model_weights.npz: The Generator neural network weights/parameters as a NumPy zip file.
format Dataset
author Leong, Wei Ji
Horgan, Huw Joseph
author_facet Leong, Wei Ji
Horgan, Huw Joseph
author_sort Leong, Wei Ji
title DeepBedMap: A super-resolution neural network created bed topography of Antarctica
title_short DeepBedMap: A super-resolution neural network created bed topography of Antarctica
title_full DeepBedMap: A super-resolution neural network created bed topography of Antarctica
title_fullStr DeepBedMap: A super-resolution neural network created bed topography of Antarctica
title_full_unstemmed DeepBedMap: A super-resolution neural network created bed topography of Antarctica
title_sort deepbedmap: a super-resolution neural network created bed topography of antarctica
publisher Zenodo
publishDate 2020
url https://dx.doi.org/10.5281/zenodo.3752613
https://zenodo.org/record/3752613
geographic Antarctic
geographic_facet Antarctic
genre Antarc*
Antarctic
Antarctica
genre_facet Antarc*
Antarctic
Antarctica
op_relation https://dx.doi.org/10.5194/tc-14-3687-2020
https://dx.doi.org/10.5281/zenodo.3752614
https://dx.doi.org/10.5281/zenodo.4054246
op_rights Open Access
GNU Lesser General Public License v3.0 or later
https://www.gnu.org/licenses/lgpl-3.0-standalone.html
lgpl-3.0+
info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.5281/zenodo.3752613
https://doi.org/10.5194/tc-14-3687-2020
https://doi.org/10.5281/zenodo.3752614
https://doi.org/10.5281/zenodo.4054246
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