Segmentation of LiDAR point cloud data in urban areas using adaptive neighborhood selection technique

D Chakraborty, EK Dey - Plos one, 2024 - journals.plos.org
Semantic segmentation of urban areas using Light Detection and Ranging (LiDAR) point
cloud data is challenging due to the complexity, outliers, and heterogeneous nature of the …

Explainable Artificial Intelligence for Machine Learning-Based Photogrammetric Point Cloud Classification

ME Atik, Z Duran, DZ Seker - IEEE Journal of Selected Topics …, 2024 - ieeexplore.ieee.org
Point clouds are one of the most widely used data sources for spatial modeling. Artificial
intelligence approaches have become an important tool for understanding and extracting …

Hierarchical heterogeneous graph learning for color-missing ALS pointcloud segmentation

B Huang, Y Zhu - Memetic Computing, 2024 - Springer
Semantically segmented aerial laser scanning (ALS) pointcloud is crucial for remote sensing
applications, offering advantages over aerial images in describing complex topography of …

Modeling the Geometry of Individual Tree Trunks Using LiDAR Data

FT Kurdi, Z Gharineiat, E Lewandowicz, J Shan - 2023 - preprints.org
Effective development of digital twins of real-world objects requires sophisticated data
collection techniques and algorithms for automated modeling of individual objects. In City …

Assessment of SLAM Scanner Accuracy for Outdoor and Indoor Surveying Tasks

Z Gharineiat, FT Kurdi, K Henny, H Gray, A Jamieson… - 2024 - preprints.org
Abstract The Simultaneous Localization And Map** (SLAM) scanner is an easy and
portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a …

A Case Survey: Internet of Things Privacy and User Awareness of Vulnerabilities

MN Lawson - 2024 - search.proquest.com
Amid the ongoing chip shortage and the prolonged effects of COVID-19 on the supply chain,
recent reports indicate that the Internet of Things (IoT) market is steadily expanding. IoT …