2 papers
cs.CV2026
Label-Efficient 3D Forest Mapping: Self-Supervised and Transfer Learning for Instance Segmentation, Semantic Segmentation, and Species Classification
Aldino Rizaldy, Fabian Ewald Fassnacht, Ahmed Jamal Afifi +3
Detailed structural and species information on individual tree level is increasingly important to support precision forestry, biodiversity conservation, and provide reference data…
cs.CV2026
3D LULC classification using multispectral LiDAR and deep learning: current and prospective schemes
Narges Takhtkeshha, Aldino Rizaldy, Markus Hollaus +3
Land Use Land Cover (LULC) classification is essential for national 3D mapping, geospatial analysis, and sustainable planning. Multispectral (MS) LiDAR provides synchronized spatia…