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Full-Text Articles in Physical Sciences and Mathematics
Semantic Segmentation Of Point Cloud Sequences Using Point Transformer V3, Marion Sisk
Semantic Segmentation Of Point Cloud Sequences Using Point Transformer V3, Marion Sisk
Master's Theses
Semantic segmentation of point clouds is a basic step for many autonomous systems including automobiles. In autonomous driving systems, LiDAR sensors are frequently used to produce point cloud sequences that allow the system to perceive the environment and navigate safely. Modern machine learning techniques for segmentation have predominately focused on single-scan segmentation, however sequence segmentation has often proven to perform better on common segmentation metrics. Using the popular Semantic KITTI dataset, we show that by providing point cloud sequences to a segmentation pipeline based on Point Transformer v3, we increase the segmentation performance between seven and fifteen percent when compared …
Automated Tree Mortality Detection Using Ubiquitously Available Public Data, Michael T. Huggins
Automated Tree Mortality Detection Using Ubiquitously Available Public Data, Michael T. Huggins
Master's Theses
Understanding the dynamic interplay between fire severity, topography, and tree mortality, is crucial for predicting future forest dynamics and enhancing resilience against climate change-induced wildfire regimes. This thesis develops a multi-sensor approach for automated estimation of tree mortality, then applies it to examine trends in tree mortality over a six-year period across a fire affected study site in the Trinity River basin in Northern California. The Random Forest model uses publicly available USGS 3D Elevation Program Lidar (3DEP) and NAIP imagery as inputs and is likely to be easily adaptable to other landscapes. The model had a Receiver Operating Characteristic …