Lei Li
PhD fellow
Machine Learning
Universitetsparken 1
2100 København Ø
1 - 2 out of 2Page size: 10
- 2022
- Published
Deep learning based 3D point cloud regression for estimating forest biomass
Oehmcke, Stefan, Li, Lei, Caballer Revenga, Jaime, Nord-Larsen, Thomas, Trepekli, Aikaterini, Gieseke, F. & Igel, Christian, 1 Nov 2022, 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2022. Renz, M., Sarwat, M., Nascimento, M. A., Shekhar, S. & Xie, X. (eds.). Association for Computing Machinery, Inc., p. 1-4 38Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods
Caballer Revenga, Jaime, Trepekli, Aikaterini, Oehmcke, Stefan, Jensen, Rasmus, Li, Lei, Igel, Christian, Gieseke, Fabian Cristian & Friborg, Thomas, 2022, In: Remote Sensing. 14, 16, 22 p., 3912.Research output: Contribution to journal › Journal article › Research › peer-review
ID: 249142638
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75
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Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
50
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Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
43
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Hierarchical Edge Aware Learning for 3D Point Cloud
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Published