Metrics
1,769,449 Downloads
Contact Share
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

371 to 380 of 1,436 Results
ltp_items.csv
May 14, 2024 - Replication Data for: Learning to predict - second language perception of reduced multi-word sequences
Comma Separated Values - 551.1 KB - MD5: 292ad87e445d936bbcd12f1df86f85fe
Includes only target items [i.e. no control and distractor items], responses marked for 'correct' (yes/no)
ltp_results.csv
May 14, 2024 - Replication Data for: Learning to predict - second language perception of reduced multi-word sequences
Comma Separated Values - 1.2 MB - MD5: 91bc683d829fbaf01b44014ee64e4b45
the complete ‘raw’ data
Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
May 10, 2024 - NTNU Colourlab
Vats, Anuja, 2024, "Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations", https://doi.org/10.18710/HSMJLL, DataverseNO, V1
The dataset comprises the pretraining and testing data for our work: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations. The pretaining data consists of images corresponding to the Digital Surface Models (DS...
00_ReadMe.txt
May 10, 2024 - Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
Plain Text - 4.9 KB - MD5: a15f845237699a3d3ef78c8b95d1bbe9
Dataset Info
ObjectImages_part_1.zip
May 10, 2024 - Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
ZIP Archive - 25.5 GB - MD5: 0e670e5a13efc3e8235e0a954c83a693
Object_images_part_2.zip
May 10, 2024 - Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
ZIP Archive - 25.4 GB - MD5: 6320ea78b2741401d0384b8ff0d7d784
segmentation_images_and_masks.zip
May 10, 2024 - Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
ZIP Archive - 9.5 GB - MD5: 2a302d08191a6d6fd6eb8086c41c41ca
TerrainImages_part_1.zip
May 10, 2024 - Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
ZIP Archive - 24.1 GB - MD5: 943b1b1125b2023f7178b688d50b9bdb
Terrain_images_part_2.zip
May 10, 2024 - Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
ZIP Archive - 20.5 GB - MD5: 264b2004851e832029fd0e27712729d2
Scripts and data for: Microorganisms in subarctic soils are depleted of ribosomes under short-, medium-, and long-term warming
Apr 23, 2024 - UiT The Arctic University of Norway
Söllinger, Andrea, 2024, "Scripts and data for: Microorganisms in subarctic soils are depleted of ribosomes under short-, medium-, and long-term warming", https://doi.org/10.18710/OW27B6, DataverseNO, V1
This dataset contains all data files and R-scripts needed to replicate the analyses presented in the manuscript: "Microorganisms in subarctic soils are depleted of ribosomes under short-, medium-, and long-term warming" The study investigates the effects of seasonal temperature d...
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.