Abstract: To address the challenges of complex structures, large organ-scale variations, and dense internal organization in plant 3D point clouds, This paper proposes Multi-PointNet++ algorithm based ...
What can you learn from other community networks? As you think about your own needs for Internet connectivity, it is helpful to understand some of the examples of the hundreds of community networks ...
Abstract: Quantum Computing (QC) technology and Deep Learning (DL) science have garnered significant attention for their potential to revolutionize computation. This paper introduces the basic ...
Abstract: In computer-assisted orthopedic surgery (CAOS), robust and accurate registration of the preoperative full bone model and the intraoperative partial point set is a prerequisite for reliable ...
Abstract: Energy efficiency is a critical concern in IEEE 802.11ah (Wi-Fi HaLow) networks, particularly in Internet of Things (IoT) scenarios where both stations (STAs) and the access point (AP) ...
Abstract: Large-scale point cloud registration is a fundamental problem for autonomous driving. To achieve alignment, most existing methods focus on local point cloud features for matching. However, ...
Anthropic is joining the increasingly crowded field of companies with AI agents that can take direct control of your local computer desktop. The company has announced that Claude Code (and its more ...
Abstract: The shape of the floating buoy of a point absorber wave energy converter (WEC) plays a crucial role in both wave energy harvesting and current drag reduction. In this study, an approach to ...
Abstract: This paper presents a novel robust and accurate normal-assisted learning-based rigid point set registration approach, i.e., Deep Bi-directional Hybrid Mixture Registration (DeepBHMR), where ...
Abstract: Multispectral LiDAR (MS-LiDAR) point cloud classification holds great potential, but current methods rely heavily on fully supervised learning, requiring costly manual labeling. To address ...
Abstract: Least-squares migration (LSM) aims to seek the best-fit solution for subsurface reflectivity with high image resolution and balanced amplitudes by minimizing the mismatching between ...