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371 to 380 of 1,441 Results
Data_Protection_Impact_Assessment_TROLLing_Lorenz_2024.pdf
May 14, 2024 - Replication Data for: Learning to predict - second language perception of reduced multi-word sequences
Adobe PDF - 382.0 KB - MD5: 22efe17edd3992a9c436d2eab7f8bf7f
Assessment of whether open publication is in line with applicable legal and research-ethical rules and guidelines
LearningToPredict_accuracy.R.txt
May 14, 2024 - Replication Data for: Learning to predict - second language perception of reduced multi-word sequences
Plain Text - 28.0 KB - MD5: 9f46891a6773b6420dc4d110540a8ad2
The R script for the model on response accuracy
LearningToPredict_Data.RData
May 14, 2024 - Replication Data for: Learning to predict - second language perception of reduced multi-word sequences
R Data - 226.1 KB - MD5: 5e950e37b770e15e595d1d3305474cbe
The data in RData format (readable in R)
LearningToPredict_GAMM_and_plots.R.txt
May 14, 2024 - Replication Data for: Learning to predict - second language perception of reduced multi-word sequences
Plain Text - 38.1 KB - MD5: 17261b4730c8cb98a26e876c2c634349
The R script for the model and graphs on response times
ltp_final.csv
May 14, 2024 - Replication Data for: Learning to predict - second language perception of reduced multi-word sequences
Comma Separated Values - 391.4 KB - MD5: 4bf0c6a15876d0ea9dba7013175b1b24
includes only correct responses on target items
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 (DSM) and Digital Terrain Models (DTM) obtained from Norway, with a groun...
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
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