Abstract: We propose a co-part segmentation method that takes a set of point clouds of the same category as input where neither a ground truth label nor a prior network is required. With difficulties ...
Target Point Cloud Segmentation for Battery Swapping Robot Based on Multiscale Attention Aggregation
Abstract: Rapid and accurate segmentation of 3-D point clouds is critical for optimizing battery-swapping robots and ensuring precise assembly. To address the challenges of computational inefficiency ...
Abstract: Uncertainty estimation for point cloud semantic segmentation is to quantify the confidence degree for the predicted label of points, which is essential for decision-making tasks. This paper ...
The Java ecosystem has historically been blessed with great IDEs to work with, including NetBeans, Eclipse and IntelliJ from JetBrains. However, in recent years Microsoft's Visual Studio Code editor ...
The Transaction Aggregator ingests financial transaction data from three simulated sources, categorises each transaction using a rules engine with optional ML fallback, persists results to PostgreSQL, ...
Abstract: In this paper, a Backward Attentive Fusing Network with Local Aggregation Classifier (BAF-LAC) is proposed to improve the performance of 3D point cloud semantic segmentation. It consists of ...
Abstract: Multi-Point Dynamic Aggregation (MPDA) is a novel task model to determine task allocation for a multi-robot system. In an MPDA scenario, several robots with different abilities aim to ...
Abstract: Point cloud analytics is poised to become a key workload on battery-powered embedded and mobile platforms in a wide range of emerging application domains, such as autonomous driving, ...
Abstract: Accurately mappingtree stems is essentialfor the analysis and estimation of tree parameters derived from terrestrial laser scanning (TLS) point clouds, including critical measurements such ...
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