2,871 to 2,880 of 7,493 Results
Jun 6, 2024 -
Background Data for: Performance improvements of supermarket R744 systems by pivoting compressor arrangements
Plain Text - 34.9 KB -
MD5: f6c79f118683331433cc5e4170278a40
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Jun 6, 2024 -
Background Data for: Performance improvements of supermarket R744 systems by pivoting compressor arrangements
PNG Image - 886.0 KB -
MD5: 5b746397cda1a7d6aaec25e1f3d05e5b
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Jun 6, 2024 -
Background Data for: Performance improvements of supermarket R744 systems by pivoting compressor arrangements
Plain Text - 291 B -
MD5: d8c504a1819ff8a7e00799df92a324ec
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Jun 6, 2024 -
Background Data for: Performance improvements of supermarket R744 systems by pivoting compressor arrangements
PNG Image - 508.7 KB -
MD5: c1df47451ca686a32e5d5e013a36cd46
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Jun 5, 2024
Veitch, Erik, 2023, "Questionnaire and interview data on passenger safety perception during autonomous ferry public trials", https://doi.org/10.18710/CFBQSN, DataverseNO, V4
Results of questionnaires and interviews conducted with passengers aboard the autonomous ferry "milliAmpere2" during field trials in period 21 Sep to 2 Oct 2022. |
Jun 5, 2024 -
Questionnaire and interview data on passenger safety perception during autonomous ferry public trials
Plain Text - 11.8 KB -
MD5: 0a22147da39a34b00a20aacfdb8af3bd
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May 10, 2024
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... |
Plain Text - 4.9 KB -
MD5: a15f845237699a3d3ef78c8b95d1bbe9
Dataset Info |
ZIP Archive - 25.5 GB -
MD5: 0e670e5a13efc3e8235e0a954c83a693
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ZIP Archive - 25.4 GB -
MD5: 6320ea78b2741401d0384b8ff0d7d784
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