258 citations · 538 across the 39 of their papers we have counts for
Showing stat.APShow all
2 papers · 1 filter
stat.AP2023★ 6 cited
Categorising the World into Local Climate Zones -- Towards Quantifying Labelling Uncertainty for Machine Learning Models
Katharina Hechinger, Xiao Xiang Zhu, Göran Kauermann
Image classification is often prone to labelling uncertainty. To generate suitable training data, images are labelled according to evaluations of human experts. This can result in…
stat.AP2023★ 18 cited
Biomass Estimation and Uncertainty Quantification from Tree Height
Qian Song, Conrad M Albrecht, Zhitong Xiong +1
We propose a tree-level biomass estimation model approximating allometric equations by LiDAR data. Since tree crown diameters estimation is challenging from spaceborne LiDAR measur…