3 papers
cs.CV2025
Mapping Semantic Segmentation to Point Clouds Using Structure from Motion for Forest Analysis
Francisco Raverta Capua, Pablo De Cristoforis
Although the use of remote sensing technologies for monitoring forested environments has gained increasing attention, publicly available point cloud datasets remain scarce due to t…
cs.RO2024
coVoxSLAM: GPU Accelerated Globally Consistent Dense SLAM
Emiliano Höss, Pablo De Cristóforis
A dense SLAM system is essential for mobile robots, as it provides localization and allows navigation, path planning, obstacle avoidance, and decision-making in unstructured enviro…
cs.CV2024
Training point-based deep learning networks for forest segmentation with synthetic data
Francisco Raverta Capua, Juan Schandin, Pablo De Cristóforis
Remote sensing through unmanned aerial systems (UAS) has been increasing in forestry in recent years, along with using machine learning for data processing. Deep learning architect…