Are we hungry for 3D LiDAR data for semantic segmentation? A survey of datasets and methods

B Gao, Y Pan, C Li, S Geng… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
3D semantic segmentation is a fundamental task for robotic and autonomous driving
applications. Recent works have been focused on using deep learning techniques, whereas …

AI-based risk assessment for construction site disaster preparedness through deep learning-based digital twinning

M Kamari, Y Ham - Automation in Construction, 2022 - Elsevier
Hurricanes are among the most devastating natural disasters in the United States, causing
billions of dollars of property damage and insured losses. During extreme wind events …

Are we hungry for 3D LiDAR data for semantic segmentation? A survey and experimental study

B Gao, Y Pan, C Li, S Geng, H Zhao - arXiv preprint arXiv:2006.04307, 2020 - arxiv.org
3D semantic segmentation is a fundamental task for robotic and autonomous driving
applications. Recent works have been focused on using deep learning techniques, whereas …

Evaluation of Class Distribution and Class Combinations on Semantic Segmentation of 3D Point Clouds With PointNet

E Barnefske, H Sternberg - Ieee Access, 2022 - ieeexplore.ieee.org
Point clouds are generated by light imaging, detection and ranging (LIDAR) scanners or
depth imaging cameras, which capture the geometry from the scanned objects with high …

Hybrid feature CNN model for point cloud classification and segmentation

X Zhang, C Fu, Y Zhao, X Xu - IET Image Processing, 2020 - Wiley Online Library
This study proposes a hybrid feature convolutional neural network (HFCNN) model for the
complete description of three‐dimensional (3D) point cloud features. The HFCNN confers …

[图书][B] Robot Learning for Loop Closure Detection and SLAM

ZS Nahman - 2019 - search.proquest.com
Robotics and autonomy continues to be a key research and development focus around the
world. Robots are increasingly prevalent in everyday life. From manufacturing, home …