Review of automatic processing of topography and surface feature identification LiDAR data using machine learning techniques
Machine Learning (ML) applications on Light Detection And Ranging (LiDAR) data have
provided promising results and thus this topic has been widely addressed in the literature …
provided promising results and thus this topic has been widely addressed in the literature …
Real-time 3D object detection and classification in autonomous driving environment using 3D LiDAR and camera sensors
The rapid development of Autonomous Vehicles (AVs) increases the requirement for the
accurate prediction of objects in the vicinity to guarantee safer journeys. For effectively …
accurate prediction of objects in the vicinity to guarantee safer journeys. For effectively …
IPCONV: Convolution with Multiple Different Kernels for Point Cloud Semantic Segmentation
R Zhang, S Chen, X Wang, Y Zhang - Remote Sensing, 2023 - mdpi.com
The segmentation of airborne laser scanning (ALS) point clouds remains a challenge in
remote sensing and photogrammetry. Deep learning methods, such as KPCONV, have …
remote sensing and photogrammetry. Deep learning methods, such as KPCONV, have …
DGPolarNet: Dynamic graph convolution network for LiDAR point cloud semantic segmentation on polar BEV
Semantic segmentation in LiDAR point clouds has become an important research topic for
autonomous driving systems. This paper proposes a dynamic graph convolution neural …
autonomous driving systems. This paper proposes a dynamic graph convolution neural …
Classification of holograms with 3D-CNN
A hologram, measured by using appropriate coherent illumination, records all substantial
volumetric information of the measured sample. It is encoded in its interference patterns and …
volumetric information of the measured sample. It is encoded in its interference patterns and …
Machine and deep learning implementations for heritage building information modelling: a critical review of theoretical and applied research
Research domain and Problem: HBIM modelling from point cloud data has become a crucial
research topic in the last decade since it is potentially considered as the central data model …
research topic in the last decade since it is potentially considered as the central data model …
Imitation Learning through Image Augmentation Using Enhanced Swin Transformer Model in Remote Sensing
Y Park, Y Sung - Remote Sensing, 2023 - mdpi.com
In unmanned systems, remote sensing is an approach that collects and analyzes data such
as visual images, infrared thermal images, and LiDAR sensor data from a distance using a …
as visual images, infrared thermal images, and LiDAR sensor data from a distance using a …
Pedestrian detection with lidar technology in smart-city deployments–challenges and recommendations
This paper describes a real case implementation of an automatic pedestrian-detection
solution, implemented in the city of Aveiro, Portugal, using affordable LiDAR technology and …
solution, implemented in the city of Aveiro, Portugal, using affordable LiDAR technology and …
Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion
R Hao, Z Wei, X He, K Zhu, J Wang, J He, L Zhang - Remote Sensing, 2022 - mdpi.com
The point cloud data from actual measurements are often sparse and incomplete, making it
difficult to apply them directly to visual processing and 3D reconstruction. The point cloud …
difficult to apply them directly to visual processing and 3D reconstruction. The point cloud …
A Robust Sphere Detection in a Realsense Point Cloud by USING Z-Score and RANSAC
LR Roman-Rivera, JC Pedraza-Ortega… - Mathematics, 2023 - mdpi.com
Three-dimensional vision cameras, such as RGB-D, use 3D point cloud to represent scenes.
File formats as XYZ and PLY are commonly used to store 3D point information as raw data …
File formats as XYZ and PLY are commonly used to store 3D point information as raw data …