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521 to 530 of 1,882 Results
Replication Data for: Dataset of motivational factors for using mobile health applications and systems
Mar 31, 2023 - UiT The Arctic University of Norway
Henriksen, André; Woldaregay, Ashenafi Zebene; Issom, David-Zacharie; Pfuhl, Gerit; Sato, Keiichi; Årsand, Eirik; Hartvigsen, Gunnar, 2023, "Replication Data for: Dataset of motivational factors for using mobile health applications and systems", https://doi.org/10.18710/AOQF05, DataverseNO, V1
This dataset contains responses from a questionnaire about what motivates people to collect and share their health data for research and public health benefits. The online questionnaire was open for data collection between November 2018 and March 2020. The questionnaire was published in a Norwegian, English and French version, and published online....
GNSS Scintillation Data (60 s) at Ny-Ålesund in 2022
Mar 30, 2023 - UiB Global Navigation Satellite System Data
Oksavik, Kjellmar, 2023, "GNSS Scintillation Data (60 s) at Ny-Ålesund in 2022", https://doi.org/10.18710/7PUEPJ, DataverseNO, V1
This data set contains phase and amplitude scintillation data at 60 seconds time resolution at Ny-Ålesund, Svalbard. The measurements were collected by the University of Bergen using a NovAtel GPStation-6 global navigation satellite system receiver. The measurements include signals from GPS, GLONASS, and GALILEO at different frequencies. These data...
GNSS Total Electron Content Data (60 s) at Ny-Ålesund in 2022
Mar 30, 2023 - UiB Global Navigation Satellite System Data
Oksavik, Kjellmar, 2023, "GNSS Total Electron Content Data (60 s) at Ny-Ålesund in 2022", https://doi.org/10.18710/WGRD0D, DataverseNO, V1
This data set contains Total Electron Content data at 60 seconds time resolution at Ny-Ålesund, Svalbard. The measurements were collected by the University of Bergen using a NovAtel GPStation-6 global navigation satellite system receiver. The measurements include signals from GPS, GLONASS, and GALILEO at different frequencies. These data are used f...
GNSS Total Electron Content Data (60 s) at Longyearbyen in 2022
Mar 30, 2023 - UiB Global Navigation Satellite System Data
Oksavik, Kjellmar, 2023, "GNSS Total Electron Content Data (60 s) at Longyearbyen in 2022", https://doi.org/10.18710/CUVRZX, DataverseNO, V1
This data set contains Total Electron Content data at 60 seconds time resolution at Kjell Henriksen Observatory (KHO) at Longyearbyen, Svalbard. The measurements were collected by the University of Bergen using a NovAtel GPStation-6 global navigation satellite system receiver. The measurements include signals from GPS, GLONASS, and GALILEO at diffe...
GNSS Total Electron Content Data (60 s) at Hopen in 2022
Mar 30, 2023 - UiB Global Navigation Satellite System Data
Oksavik, Kjellmar, 2023, "GNSS Total Electron Content Data (60 s) at Hopen in 2022", https://doi.org/10.18710/9X52WA, DataverseNO, V1
This data set contains Total Electron Content data at 60 seconds time resolution at Hopen, Svalbard. The measurements were collected by the University of Bergen using a NovAtel GPStation-6 global navigation satellite system receiver. The measurements include signals from GPS, GLONASS, and GALILEO at different frequencies. These data are used for re...
GNSS Total Electron Content Data (60 s) at Bjørnøya in 2022
Mar 30, 2023 - UiB Global Navigation Satellite System Data
Oksavik, Kjellmar, 2023, "GNSS Total Electron Content Data (60 s) at Bjørnøya in 2022", https://doi.org/10.18710/SKQUTL, DataverseNO, V1
This data set contains Total Electron Content data at 60 seconds time resolution from Bjørnøya, Svalbard. The measurements were collected by the University of Bergen using a NovAtel GPStation-6 global navigation satellite system receiver. The measurements include signals from GPS, GLONASS, and GALILEO at different frequencies. These data are used f...
GNSS Scintillation Data (60 s) at Longyearbyen in 2022
Mar 30, 2023 - UiB Global Navigation Satellite System Data
Oksavik, Kjellmar, 2023, "GNSS Scintillation Data (60 s) at Longyearbyen in 2022", https://doi.org/10.18710/KMPO6N, DataverseNO, V1
This data set contains phase and amplitude scintillation data at 60 seconds time resolution at Kjell Henriksen Observatory (KHO) at Longyearbyen, Svalbard. The measurements were collected by the University of Bergen using a NovAtel GPStation-6 global navigation satellite system receiver. The measurements include signals from GPS, GLONASS, and GALIL...
GNSS Scintillation Data (60 s) at Bjørnøya in 2022
Mar 30, 2023 - UiB Global Navigation Satellite System Data
Oksavik, Kjellmar, 2023, "GNSS Scintillation Data (60 s) at Bjørnøya in 2022", https://doi.org/10.18710/MWVQFD, DataverseNO, V1
This data set contains phase and amplitude scintillation data at 60 seconds time resolution at Bjørnøya, Svalbard. The measurements were collected by the University of Bergen using a NovAtel GPStation-6 global navigation satellite system receiver. The measurements include signals from GPS, GLONASS, and GALILEO at different frequencies. These data a...
GNSS Scintillation Data (60 s) at Hopen in 2022
Mar 30, 2023 - UiB Global Navigation Satellite System Data
Oksavik, Kjellmar, 2023, "GNSS Scintillation Data (60 s) at Hopen in 2022", https://doi.org/10.18710/EMJBEO, DataverseNO, V1
This data set contains phase and amplitude scintillation data at 60 seconds time resolution at Hopen, Svalbard. The measurements were collected by the University of Bergen using a NovAtel GPStation-6 global navigation satellite system receiver. The measurements include signals from GPS, GLONASS, and GALILEO at different frequencies. These data are...
Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images
Mar 29, 2023 - UiT The Arctic University of Norway
Gupta, Deepak K.; Bhamba, Udbhav; Thakur, Abhishek; Gupta, Akash; Sharan, Suraj; Demir, Ertugrul; Prasad, Dilip K., 2023, "Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images", https://doi.org/10.18710/4F4KJS, DataverseNO, V1
Convolutional neural network (CNN) approaches available in the current literature are designed to work primarily with low-resolution images. When applied on very large images, challenges related to GPU memory, smaller receptive field than needed for semantic correspondence and the need to incorporate multi-scale features arise. The resolution of in...
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