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: This paper describes a method for discriminating structures in a nuclear facility based on deep learning using three-dimensional (3D) point cloud data. To promote safe and secure ...

Abstract: Obtaining complete point cloud data is the basis of rock surface segmentation and related rock-mass numerical simulation. The existing rock-mass point cloud registration methods usually ...

Abstract: Point clouds can capture the precise geometric information of objects and scenes, which are an important source of 3-D data and one of the most popular 3-D geometric data structures for ...

Abstract: Domain adaptive LiDAR point cloud segmentation aims to develop an effective target segmentation model using labeled source data and unlabeled target data. Existing domain adaptation methods ...

Abstract: In recent years, there has been a rapid growth in applications that rely on point clouds to represent the 3D world, driven by the increasing demand for immersive and other related scenarios.

Liz Simmons is an education staff writer at Forbes Advisor. She has written about higher education and career development for various online publications since 2016. She earned a master’s degree in ...

Abstract: As a crucial representation of 3D data, a point cloud (PC) can accurately capture the geometry, structure, and color information of objects. However, various quality problems arise owing to ...

Many Americans are concerned about the health of the labor market, and for good reason. Job growth turned negative during the summer, unemployment-insurance claims have been rising, and there are more ...

What are lock-free data structures? Lock-free data structures are data structures that are thread and interrupt safe for concurrent use without having to use mutual exclusion mechanisms. They are most ...