1 to 10 of 121 Results
Feb 19, 2024
Vallejo Orti, Miguel; Anders, Katharina; Ajali, Oliubikum; Bubenzer, Olaf; Höfle, Bernhard, 2024, "Integrating VGI contributions for gully mapping using Kalman filter and machine learning", https://doi.org/10.11588/data/UHSQG0, heiDATA, V1, UNF:6:dbfZe/C8CmWXcBEZJg2RPw== [fileUNF]
The codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of... |
Feb 19, 2024 -
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
ZIP Archive - 1.9 MB -
MD5: 4833cdc615e69607bd51b49cfff7ea9d
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Feb 19, 2024 -
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
Python Source Code - 23.7 KB -
MD5: 9b1919e5bf0dcdcf8e3d68eec4a25fdd
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Feb 19, 2024 -
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
Plain Text - 2.7 KB -
MD5: 3592aa831001b5a26154a7ba6c3109fd
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Feb 19, 2024 -
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
Tabular Data - 31.6 KB - 8 Variables, 463 Observations - UNF:6:dbfZe/C8CmWXcBEZJg2RPw==
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Feb 19, 2024 -
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
Plain Text - 7.0 KB -
MD5: 9b20b45da9830b79f92dc506546496f1
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Feb 19, 2024 -
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
ZIP Archive - 3.9 MB -
MD5: 96697ceeebf0cca5a98e4c07ffbdd54a
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Feb 19, 2024 -
Integrating VGI contributions for gully mapping using Kalman filter and machine learning
ZIP Archive - 15.4 KB -
MD5: 6001d045b9acf3b143b7df82c4ca0c89
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Jan 18, 2024
Weiser, Hannah; Ulrich, Veit; Winiwarter, Lukas; Esmorís, Alberto M.; Höfle, Bernhard, 2024, "Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation", https://doi.org/10.11588/data/UUMEDI, heiDATA, V1, UNF:6:9U7BGTgjjsWd1GduT1qXjA== [fileUNF]
This dataset contains 11 terrestrial laser scanning (TLS) tree point clouds (in .LAZ format v1.4) of 7 different species, which have been manually labeled into leaf and wood points. The labels are contained in the Classification field (0 = wood, 1 = leaf). The point clouds have a... |
Jan 18, 2024 -
Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation
Unknown - 78.2 MB -
MD5: 984abea0c7e1e0ebacfa92bf974a101e
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