41 to 50 of 104 Results
Dec 9, 2021 -
Improving change analysis from near-continuous 3D time series by considering full temporal information [Data and Source Code]
Plain Text - 706 B -
MD5: c552c6f024c509ebdf1123f8a8dfa8ba
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Dec 9, 2021 -
Improving change analysis from near-continuous 3D time series by considering full temporal information [Data and Source Code]
ZIP Archive - 25.8 KB -
MD5: a9797415a92bc37c37a6a3fbbe386be8
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Jan 25, 2022 -
Correspondence-driven plane-based M3C2 for quantification of 3D topographic change with lower uncertainty [Data and Source Code]
ZIP Archive - 376.5 KB -
MD5: 1f7af2216c7548e34a58e73df5c62fb4
Contains "outcrop.exe" and "ANN.dll". |
JSON - 312 B -
MD5: a5835047e1a69987e02599d7fc1821c6
Filter pipeline for segments of class "paddy field". |
JSON - 300 B -
MD5: 1fe264da9d9691837fb718f99cf96803
Filter pipeline for segments of class "slope" and "ridge". |
JSON - 563 B -
MD5: 5f845e8634511fea8aa1cde9d3ad288f
Filter pipeline for segments of class "valley". |
Unknown - 77.7 MB -
MD5: e9b080ab871e5a96a31c73179235dd9e
Input data: 3D point cloud from the sample region to which the filters are applied with the AFwizard. |
GeoJSON - 18.4 KB -
MD5: cb34ffb4e3214f613330c72a9093c120
Segmentation of the sample area with segment classes and the adapted filter pipelines assigned. |
GeoJSON - 26.4 KB -
MD5: f352d25ba4ca4139a94d478d0fdfa6a5
Input data: Segmentation of the sample area with segment classes but without filter pipelines assigned. |
Unknown - 4.0 MB -
MD5: ecb287c259ef82ed4e449f718abf8abf
3D point cloud of a sub-area that represents segments of class "paddy". |