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1,781 to 1,790 of 2,876 Results
General_Calculations_O_and_ M_ Dogger_Bank.csv
May 16, 2024 - Supplementary Materials-Life Cycle Assessment of Offshore Wind Farms – A Comparative Study of Floating Vs. Fixed Offshore Wind Turbines-Master Thesis-Omid Lotfizadeh
Comma Separated Values - 14.3 KB - MD5: 2c80bd3a490ec556f72b36a287315f90
General_Calculations_O_and_ M_ Dogger_Bank.csv
General_Calculations_O_and_ M_Hywind_Tampen.csv
May 16, 2024 - Supplementary Materials-Life Cycle Assessment of Offshore Wind Farms – A Comparative Study of Floating Vs. Fixed Offshore Wind Turbines-Master Thesis-Omid Lotfizadeh
Comma Separated Values - 13.2 KB - MD5: 0cc48795468de392373512724e307d6c
General_Calculations_O_and_ M_Hywind_Tampen.csv
Inventory_Dogger_Bank_BFOWF.csv
May 16, 2024 - Supplementary Materials-Life Cycle Assessment of Offshore Wind Farms – A Comparative Study of Floating Vs. Fixed Offshore Wind Turbines-Master Thesis-Omid Lotfizadeh
Comma Separated Values - 1.4 MB - MD5: 4887e31d9204bf36958ab68d157c237b
Inventory_Dogger_Bank_BFOWF.csv
Inventory_Hywind_Tampen_FOWF.csv
May 16, 2024 - Supplementary Materials-Life Cycle Assessment of Offshore Wind Farms – A Comparative Study of Floating Vs. Fixed Offshore Wind Turbines-Master Thesis-Omid Lotfizadeh
Comma Separated Values - 6.9 KB - MD5: 751754ad5d654b496b024bffcf120fea
Inventory_Hywind_Tampen_FOWF.csv
ReadMe_file.txt
May 16, 2024 - Supplementary Materials-Life Cycle Assessment of Offshore Wind Farms – A Comparative Study of Floating Vs. Fixed Offshore Wind Turbines-Master Thesis-Omid Lotfizadeh
Plain Text - 3.3 KB - MD5: 6adc4fa4260c40b9e4f683b5ac070acb
ReadMe_file.txt
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
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
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