Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm
Abstract Machine learning (ML) has shown to be an effective alternative to physical models
for quality prediction and process optimization of metal additive manufacturing (AM) …
for quality prediction and process optimization of metal additive manufacturing (AM) …
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 …
An improved RANSAC for 3D point cloud plane segmentation based on normal distribution transformation cells
L Li, F Yang, H Zhu, D Li, Y Li, L Tang - Remote Sensing, 2017 - mdpi.com
Plane segmentation is a basic task in the automatic reconstruction of indoor and urban
environments from unorganized point clouds acquired by laser scanners. As one of the most …
environments from unorganized point clouds acquired by laser scanners. As one of the most …
Quantifying rooftop photovoltaic solar energy potential: A machine learning approach
The need for reduction in CO 2 emissions to mitigate global warming has resulted in
increasing use of renewable energy sources. In urban areas, solar photovoltaic (PV) …
increasing use of renewable energy sources. In urban areas, solar photovoltaic (PV) …
Segmentation and reconstruction of polyhedral building roofs from aerial lidar point clouds
This paper presents a solution framework for the segmentation and reconstruction of
polyhedral building roofs from aerial LIght Detection And Ranging (lidar) point clouds. The …
polyhedral building roofs from aerial LIght Detection And Ranging (lidar) point clouds. The …
2D image-to-3D model: Knowledge-based 3D building reconstruction (3DBR) using single aerial images and convolutional neural networks (CNNs)
In this study, a deep learning (DL)-based approach is proposed for the detection and
reconstruction of buildings from a single aerial image. The pre-required knowledge to …
reconstruction of buildings from a single aerial image. The pre-required knowledge to …
Investigation on the weighted ransac approaches for building roof plane segmentation from lidar point clouds
RANdom SAmple Consensus (RANSAC) is a widely adopted method for LiDAR point cloud
segmentation because of its robustness to noise and outliers. However, RANSAC has a …
segmentation because of its robustness to noise and outliers. However, RANSAC has a …
3D modeling and visualization of single tree Lidar point cloud using matrixial form
Tree modeling and visualization still represent a challenge in the light detecting and ranging
area. Starting from the segmented tree point clouds, this article presents an innovative tree …
area. Starting from the segmented tree point clouds, this article presents an innovative tree …
Automatic roof plane detection and analysis in airborne lidar point clouds for solar potential assessment
A relative height threshold is defined to separate potential roof points from the point cloud,
followed by a segmentation of these points into homogeneous areas fulfilling the defined …
followed by a segmentation of these points into homogeneous areas fulfilling the defined …
Model driven reconstruction of roofs from sparse LIDAR point clouds
This article presents a novel, fully automatic method for the reconstruction of three-
dimensional building models with prototypical roofs (CityGML LoD2) from LIDAR data and …
dimensional building models with prototypical roofs (CityGML LoD2) from LIDAR data and …