Baltic Sea Ice Dataset ...
The "Baltic Sea Ice Dataset" encompasses a comprehensive collection of visible and infrared images, and their labels, along with GNSS trajectory for Sampo ship, gathered from multiple data collection campaigns conducted in icy waters around Finland during February and March of 2021 and 202...
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2024
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Online Access: | https://dx.doi.org/10.5281/zenodo.10843469 https://zenodo.org/doi/10.5281/zenodo.10843469 |
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ftdatacite:10.5281/zenodo.10843469 2024-04-28T08:25:14+00:00 Baltic Sea Ice Dataset ... Gorad, Ajinkya Hammarberg, Toni Ramm-Schmidt, Henrik Särkkä, Simo 2024 https://dx.doi.org/10.5281/zenodo.10843469 https://zenodo.org/doi/10.5281/zenodo.10843469 unknown Zenodo https://dx.doi.org/10.5281/zenodo.10843470 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 dataset Dataset 2024 ftdatacite https://doi.org/10.5281/zenodo.1084346910.5281/zenodo.10843470 2024-04-02T11:48:34Z The "Baltic Sea Ice Dataset" encompasses a comprehensive collection of visible and infrared images, and their labels, along with GNSS trajectory for Sampo ship, gathered from multiple data collection campaigns conducted in icy waters around Finland during February and March of 2021 and 2022. The dataset captures diverse sea ice conditions and navigational scenarios from four distinct locations in the Baltic Sea, including the Gulf of Finland on the Tallinn-Helsinki route, near Helsinki across the Katajanokka-Suomenlinna route, from the Sampo icebreaker tour at Kemi, and a ferry route across Hailuoto-Oulu. Images were obtained using a variety of equipment, including FLIR Blackfly visible range cameras, Nikon DSLR 3300, smartphones, and a Raymarine FLIR M232 thermal infrared camera, ensuring a diverse dataset for the development of situational awareness systems for autonomous navigation in icy waters. A subset of this dataset has been labeled with 13 classes to include several ice types, such as level ice, ... Dataset Icebreaker Sea ice DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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description |
The "Baltic Sea Ice Dataset" encompasses a comprehensive collection of visible and infrared images, and their labels, along with GNSS trajectory for Sampo ship, gathered from multiple data collection campaigns conducted in icy waters around Finland during February and March of 2021 and 2022. The dataset captures diverse sea ice conditions and navigational scenarios from four distinct locations in the Baltic Sea, including the Gulf of Finland on the Tallinn-Helsinki route, near Helsinki across the Katajanokka-Suomenlinna route, from the Sampo icebreaker tour at Kemi, and a ferry route across Hailuoto-Oulu. Images were obtained using a variety of equipment, including FLIR Blackfly visible range cameras, Nikon DSLR 3300, smartphones, and a Raymarine FLIR M232 thermal infrared camera, ensuring a diverse dataset for the development of situational awareness systems for autonomous navigation in icy waters. A subset of this dataset has been labeled with 13 classes to include several ice types, such as level ice, ... |
format |
Dataset |
author |
Gorad, Ajinkya Hammarberg, Toni Ramm-Schmidt, Henrik Särkkä, Simo |
spellingShingle |
Gorad, Ajinkya Hammarberg, Toni Ramm-Schmidt, Henrik Särkkä, Simo Baltic Sea Ice Dataset ... |
author_facet |
Gorad, Ajinkya Hammarberg, Toni Ramm-Schmidt, Henrik Särkkä, Simo |
author_sort |
Gorad, Ajinkya |
title |
Baltic Sea Ice Dataset ... |
title_short |
Baltic Sea Ice Dataset ... |
title_full |
Baltic Sea Ice Dataset ... |
title_fullStr |
Baltic Sea Ice Dataset ... |
title_full_unstemmed |
Baltic Sea Ice Dataset ... |
title_sort |
baltic sea ice dataset ... |
publisher |
Zenodo |
publishDate |
2024 |
url |
https://dx.doi.org/10.5281/zenodo.10843469 https://zenodo.org/doi/10.5281/zenodo.10843469 |
genre |
Icebreaker Sea ice |
genre_facet |
Icebreaker Sea ice |
op_relation |
https://dx.doi.org/10.5281/zenodo.10843470 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.5281/zenodo.1084346910.5281/zenodo.10843470 |
_version_ |
1797585090366144512 |