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2,511 to 2,520 of 13,198 Results
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 Effect of scalding temperature on sensory and biochemical properties in a hard goat milk cheese.
May 13, 2024 - Norwegian University of Life Sciences (NMBU)
Bjørgan, Beate, 2024, "Replication Data for Effect of scalding temperature on sensory and biochemical properties in a hard goat milk cheese.", https://doi.org/10.18710/2HDGGA, DataverseNO, V1
A procedure to produce a hard cheese made from goat milk set to approach Manchego cheese was developed. Also investigated was how a slight difference in scalding temperature affects the chemical and sensory properties of the cheeses during the ripening process.The cheese was made by applying two different scalding temperatures (38 °C and 40 °C) in...
00_Readme.txt
May 13, 2024 - Replication Data for Effect of scalding temperature on sensory and biochemical properties in a hard goat milk cheese.
Plain Text - 3.4 KB - MD5: dc0d374321243014a316b998dcf593c0
01_Cheese_analysis.txt
May 13, 2024 - Replication Data for Effect of scalding temperature on sensory and biochemical properties in a hard goat milk cheese.
Plain Text - 10.6 KB - MD5: a1cab199591e027eaf06d9bf44ae5866
Replication Data for: Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
May 10, 2024 - NTNU – Norwegian University of Science and Technology
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
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
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