The global demand for food and bioenergy changes associated with land use and land
cover change (LULCC) has raised concerns about the environment, global warming, and …

Point clouds are increasingly being used to improve productivity, quality, and safety
throughout the life cycle of construction and infrastructure projects. While applicable for …

The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …

Currently, single-stage point-based 3D object detection network remains underexplored.
Many approaches worked on point cloud space without optimization and failed to capture …

As an important application in remote sensing, landcover classification remains one of the
most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly …

3D segmentation is a fundamental and challenging problem in computer vision with
applications in autonomous driving, robotics, augmented reality and medical image …

3D semantic segmentation is a fundamental task for robotic and autonomous driving
applications. Recent works have been focused on using deep learning techniques, whereas …

In the cultural heritage field, point clouds, as important raw data of geomatics, are not only
three-dimensional (3D) spatial presentations of 3D objects but they also have the potential …

Scalable systems for automated driving have to reliably cope with an open-world setting.
This means, the perception systems are exposed to drastic domain shifts, like changes in …

Mechanical, electrical and plumbing (MEP) system provides various services and creates
comfortable environments to residents in cities. To enhance the management efficiency of …