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1,341 to 1,350 of 1,364 Results

07_SDG13_BTA_Searchstring_2019-11-18.txt May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results? Plain Text - 5.4 KB - MD5: bb110dbcba0025bc997392aaa5fa7cb4
07_SDG13_Searchstring_2019-11-18.tab May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results? Tabular Data - 8.9 KB - 6 Variables, 87 Observations - UNF:6:FVh5zrY7tORx08qyzv3n9g== SDG 13 - Climate Action
08_SDG14_BAA_Searchstring_2019-11-18.txt May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results? Plain Text - 28.8 KB - MD5: 2ab5e6239de6ea114055ce320efe9fc1
08_SDG14_BTA_Searchstring_2019-11-18.txt May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results? Plain Text - 21.8 KB - MD5: 4e9bce5e7963beca698383915bd120e1
08_SDG14_Searchstring_2019-11-18.tab May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results? Tabular Data - 33.5 KB - 8 Variables, 422 Observations - UNF:6:3CKeLUw/5wh2XrRpxpaDBw== SDG 14 - Life below water
Replication Data for: Auroral Image Classification with Deep Neural Networks Apr 14, 2020 - UiT The Arctic University of Norway Kvammen, Andreas; Wickstrøm, Kristoffer; McKay, Derek; Partamies, Noora, 2020, "Replication Data for: Auroral Image Classification with Deep Neural Networks", https://doi.org/10.18710/SSA38J, DataverseNO, V3 Results from a study of automatic aurora classification using machine learning techniques are presented. The aurora is the manifestation of physical phenomena in the ionosphere magnetosphere environment. Automatic classification of millions of auroral images from the Arctic and A...
00_ReadMe.txt Apr 14, 2020 - Replication Data for: Auroral Image Classification with Deep Neural Networks Plain Text - 4.6 KB - MD5: 6c25a3fdae5cc8db0938a055991b217e ReadMe file where dataset and the files in repository is described.
TestImages.zip Apr 14, 2020 - Replication Data for: Auroral Image Classification with Deep Neural Networks ZIP Archive - 10.2 MB - MD5: b1ff172b00f06c86dd82c021683d451e Zipped archive containing the test images of the dataset in .PNG format. The class of the image is included in the image title.
TrainingImages.zip Apr 14, 2020 - Replication Data for: Auroral Image Classification with Deep Neural Networks ZIP Archive - 35.8 MB - MD5: b27e63cd55a51e756d0c387a1b7be893 Zipped archive containing the training images of the dataset in .PNG format. The class of the image is included in the image title.
Water sources in the Syrian Desert Jan 24, 2020 - University of Bergen Seland, Eivind Heldaas, 2019, "Water sources in the Syrian Desert", https://doi.org/10.18710/CEY9QR, DataverseNO, V2 The dataset gives the location of 2236 water sources in the Syrian Desert, which were identified on Soviet topographic maps originally printed in 1980. These consist of 853 pools/reservoirs/cisterns, 1061 small wells, 119 large wells and 203 springs, and represent a complete cove...

07_SDG13_BTA_Searchstring_2019-11-18.txt

May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results?

Plain Text - 5.4 KB -

07_SDG13_Searchstring_2019-11-18.tab

May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results?

Tabular Data - 8.9 KB - 6 Variables, 87 Observations -

SDG 13 - Climate Action

08_SDG14_BAA_Searchstring_2019-11-18.txt

May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results?

Plain Text - 28.8 KB -

08_SDG14_BTA_Searchstring_2019-11-18.txt

May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results?

Plain Text - 21.8 KB -

08_SDG14_Searchstring_2019-11-18.tab

May 25, 2020 - Replication data for: Mapping scholarly publications related to the Sustainable Development Goals: Do independent bibliometric approaches get the same results?

Tabular Data - 33.5 KB - 8 Variables, 422 Observations -

SDG 14 - Life below water

Replication Data for: Auroral Image Classification with Deep Neural Networks

Apr 14, 2020 - UiT The Arctic University of Norway

Kvammen, Andreas; Wickstrøm, Kristoffer; McKay, Derek; Partamies, Noora, 2020, "Replication Data for: Auroral Image Classification with Deep Neural Networks", https://doi.org/10.18710/SSA38J, DataverseNO, V3

Results from a study of automatic aurora classification using machine learning techniques are presented. The aurora is the manifestation of physical phenomena in the ionosphere magnetosphere environment. Automatic classification of millions of auroral images from the Arctic and A...

00_ReadMe.txt

Apr 14, 2020 - Replication Data for: Auroral Image Classification with Deep Neural Networks

Plain Text - 4.6 KB -

ReadMe file where dataset and the files in repository is described.

TestImages.zip

Apr 14, 2020 - Replication Data for: Auroral Image Classification with Deep Neural Networks

ZIP Archive - 10.2 MB -

Zipped archive containing the test images of the dataset in .PNG format. The class of the image is included in the image title.

TrainingImages.zip

Apr 14, 2020 - Replication Data for: Auroral Image Classification with Deep Neural Networks

ZIP Archive - 35.8 MB -

Zipped archive containing the training images of the dataset in .PNG format. The class of the image is included in the image title.

Water sources in the Syrian Desert

Jan 24, 2020 - University of Bergen

Seland, Eivind Heldaas, 2019, "Water sources in the Syrian Desert", https://doi.org/10.18710/CEY9QR, DataverseNO, V2

The dataset gives the location of 2236 water sources in the Syrian Desert, which were identified on Soviet topographic maps originally printed in 1980. These consist of 853 pools/reservoirs/cisterns, 1061 small wells, 119 large wells and 203 springs, and represent a complete cove...

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