3 papers
cs.CV2026
Through the Perspective of LiDAR: A Feature-Enriched and Uncertainty-Aware Annotation Pipeline for Terrestrial Point Cloud Segmentation
Fei Zhang, Rob Chancia, Josie Clapp +4
Accurate semantic segmentation of terrestrial laser scanning (TLS) point clouds is limited by costly manual annotation. We propose a semi-automated, uncertainty-aware pipeline that…
cs.CV2025
Deep Imbalanced Multi-Target Regression: 3D Point Cloud Voxel Content Estimation in Simulated Forests
Amirhossein Hassanzadeh, Bartosz Krawczyk, Michael Saunders +4
Voxelization is an effective approach to reduce the computational cost of processing Light Detection and Ranging (LiDAR) data, yet it results in a loss of fine-scale structural inf…
physics.geo-ph2025
Development of an Uncertainty Workflow to Support Landsat TIRS Split Window-Derived Surface Temperature Products
Amirhossein Hassanzadeh, Robert Mancini, Aaron Gerace +2
Current Landsat Level 2 surface temperature products are derived using a single-channel (SC) methodology to estimate per-pixel surface temperature (ST) maps from Level~1 radiance d…