Looking for TROLLing? Click here: https://trolling.uit.no/
Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

2,201 to 2,210 of 11,076 Results
02_Swedish-observations-of-the-aurora-borealis_1716-1732.csv
Apr 4, 2023 - Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications
Comma Separated Values - 39.7 KB - MD5: 0df96f5eb3da3a5538d6b52320a4f2b1
Dataset file
Replication Data for: Dataset of motivational factors for using mobile health applications and systems
Mar 31, 2023
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 publi...
00_ReadMe.txt
Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems
Plain Text - 23.1 KB - MD5: d29a0fa833e1d0878531dd44fccd154a
Question-metadata.csv
Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems
Comma Separated Values - 26.1 KB - MD5: d2413d54d36192d98442c49e22bdd9f0
Describes which answer options are available for each question
Questionnaire.pdf
Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems
Adobe PDF - 142.7 KB - MD5: bdc00c7afcaca72a27f9e4be30b87114
Responses.csv
Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems
Comma Separated Values - 281.0 KB - MD5: c3b1ace55b8d7348abe8c22d7b8b6039
Questionnaire responses
Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images
Mar 29, 2023
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 th...
00_ReadMe.txt
Mar 29, 2023 - Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images
Plain Text - 6.2 KB - MD5: 66b4fc3733f5c54175c57f7c40d24869
test.zip
Mar 29, 2023 - Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images
ZIP Archive - 8.7 GB - MD5: 776f8bccbb1285032864afee9cfa991b
train.csv
Mar 29, 2023 - Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images
Comma Separated Values - 373.1 KB - MD5: acd730388d00a1102f17a8139106ac42
For testing purposes you may contact Dilip K. Prasad at dilip.prasad@uit.no
Add Data

Log in to create a dataverse or add a dataset.

Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.