Abstract: Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks continue to pose significant threats to networked systems, causing disruptions that can lead to substantial financial ...

Abstract: Downsampling is a crucial task for processing large scale and/or dense point clouds with limited resources. Owing to the development of deep learning, approaches of task-oriented point cloud ...

Abstract: The self-attention (SA) network revisits the essence of data and has achieved remarkable results in text processing and image analysis. SA is conceptualized as a set operator that is ...

Abstract: With the rapid advancement of three-dimensional (3D) sensing technology, point cloud has emerged as one of the most important approaches for representing 3D data. However, quality ...

Abstract: Existing airborne laser scanning (ALS) point cloud semantic segmentation approaches are limited by their overreliances on sufficient point-wise annotations that further confine their ...

The advent of the sixth-generation (6G) networks presents another round of revolution for the mobile communication landscape, promising an immersive experience, robust reliability, minimal latency, ...

Abstract: Statistical models of inter-point distances are pivotal for analyzing and optimizing wireless communication networks and other spatial systems, such as vehicular swarms and distributed ...

Abstract: Deep Neural Networks (DNNs) impose significant computational demands, necessitating optimizations for computational and energy efficiencies. Per-vector scaling, which applies a scaling ...

Abstract: The inherent limitations in scaling up ground infrastructure for future wireless networks, combined with decreasing operational costs of aerial and space networks, are driving considerable ...

Abstract: Space-air-ground integrated networks (SAGINs) face unprecedented security challenges due to their inherent characteristics, such as multidimensional heterogeneity and dynamic topologies.