Abstract: The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Transformer ...

Abstract: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex ...

Abstract: Global Navigation Satellite Systems (GNSS) are crucial for intelligent transportation systems (ITS), providing essential positioning capabilities globally. However, in urban canyons, the ...

Abstract: The arbitrary-oriented ship detection in synthetic aperture radar (SAR) imagery remains especially challenging due to multiscale imbalance and the characteristics of SAR imaging, a problem ...

Abstract: Existing object-level simultaneous localization and mapping (SLAM) methods often overlook the correspondence between semantic information and geometric features, resulting in a significant ...

Abstract: In recent years, Large Language Models (LLMs) have shown great abilities in various tasks, including question answering, arithmetic problem solving, and poetry writing, among others.

Abstract: The rapidly growing importance of machine learning (ML) applications, coupled with their ever-increasing model size and inference energy footprint, has created a strong need for specialized ...

Abstract: This paper proposes V2Sim, an open source Pythonbased simulation platform designed for advanced vehicle-togrid (V2G) analysis in coupled urban power and transportation networks. By ...

Abstract: Current RGB-D methods usually leverage large-scale backbones to improve accuracy but sacrifice efficiency. Meanwhile, several existing lightweight methods are difficult to achieve ...

Abstract: In the semantic segmentation of remote sensing images, methods based on convolutional neural networks (CNNs) and Transformers have been extensively studied. Nevertheless, CNN struggles to ...

Abstract: Optical wireless integrated sensing and communication (OW-ISAC) is emerging as a crucial technology to complement and augment its radio-frequency counterpart. In this paper, we propose an ...

Abstract: Deep learning has become increasingly popular in hyperspectral image (HSI) and light detection and ranging (LiDAR) data classification, thanks to its powerful feature learning and ...