3 papers
cs.CV2025
BarkXAI: A Lightweight Post-Hoc Explainable Method for Tree Species Classification with Quantifiable Concepts
Yunmei Huang, Songlin Hou, Zachary Nelson Horve +1
The precise identification of tree species is fundamental to forestry, conservation, and environmental monitoring. Though many studies have demonstrated that high accuracy can be a…
cs.CV2024
Unsupervised Machine Learning for Detecting and Locating Human-Made Objects in 3D Point Cloud
Hong Zhao, Huyunting Huang, Tonglin Zhang +3
A 3D point cloud is an unstructured, sparse, and irregular dataset, typically collected by airborne LiDAR systems over a geological region. Laser pulses emitted from these systems…
cs.CV2024
Tree-D Fusion: Simulation-Ready Tree Dataset from Single Images with Diffusion Priors
Jae Joong Lee, Bosheng Li, Sara Beery +4
We introduce Tree D-fusion, featuring the first collection of 600,000 environmentally aware, 3D simulation-ready tree models generated through Diffusion priors. Each reconstructed…