Abstract: Submerged aquatic vegetation (SAV) is crucial for maintaining a clear-water state in lakes. Tracking the spatiotemporal changes in SAV is crucial for understanding the ecological evolution, ...

Abstract: LiDAR point cloud data is essential in autonomous driving, robotic navigation, and 3D modeling. However, noise caused by sensor errors and environmental factors degrades data quality and ...

Abstract: The demand for 3D scanning of workpiece geometries in automated assembly within workshops is increasingly critical, playing a vital role in the process. Point cloud registration, as an ...

Abstract: Semantic segmentation of point clouds is an essential task for understanding the environment in autonomous driving and robotics. Recent range-based works achieve real-time efficiency, while ...

Abstract: With the rapid advancement of technology, there is an increasing need for quick and accurate analysis of vehicle accident severity, determination of accident liability, assessment of vehicle ...

Spot market rates are slowly improving, suggesting a recovery may be underway. That’s the good news. The bad news for those in the trailer industry is that demand remains weak and fleets seem set on ...

Abstract: The extensive adoption of cloud computing platforms in storing and processing data have brought forth a new age of efficiency in the way data is stored, processed and managed, requiring new ...

Abstract: In industrial equipment maintenance, acoustic monitoring offers an effective non-contact approach for anomaly detection. However, deep learning-based methods typically require large ...

Shortest path algorithms sit at the heart of modern graph theory and many of the systems that move people, data, and goods around the world. After nearly seventy years of relying on the same classic ...

Introduction: Three-dimensional (3D) point clouds acquired by LiDAR are fundamental for applications such as autonomous navigation, mobile robotics, infrastructure inspection, and cultural-heritage ...