Abstract: Collaborative perception is essential to address occlusion and sensor failure issues in autonomous driving. In recent years, theoretical and experimental investigations of novel works for ...

Abstract: The light absorption and scattering of underwater impurities lead to poor underwater imaging quality. The existing data-driven based underwater image enhancement (UIE) techniques suffer from ...

Abstract: 6G and beyond will fulfill the requirements of a fully connected world and provide ubiquitous wireless connectivity for all. Transformative solutions are expected to drive the surge for ...

Abstract: Recently, the multiscale problem in computer vision has gradually attracted people’s attention. This article focuses on multiscale representation for object detection and recognition, ...

Abstract: Enhancing the efficiency and the reliability of the data center are the technical challenges for maintaining the quality of services for the end-users in the data center operation. The ...

Abstract: POSIX.1-2024 is simultaneously IEEE Std 1003.1™-2024 and The Open Group Standard Base Specifications, Issue 8. POSIX.1-2024 defines a standard operating system interface and environment, ...

Abstract: In the manufacturing process of hot-rolled steel strips, various mechanical forces, and environmental conditions can cause surface defects, making their detection crucial for ensuring ...

Abstract: Low Earth Orbit (LEO) satellites have emerged as crucial enablers of direct connections with remote terrestrial terminals. However, energy limitations and insufficient antenna capabilities ...

Abstract: To better characterize the differences in category features in Facial Expression Recognition (FER) tasks, and improve inter-class separability and intra-class compactness, we propose a ...

Abstract: The accurate lifetime prediction of lithium-ion batteries (LIBs) is essential to the normal and effective operation of electric devices. However, such estimation faces huge challenges due to ...

Abstract: Autonomous driving has achieved significant milestones in research and development over the last two decades. There is increasing interest in the field as the deployment of autonomous ...

Abstract: Cluster analysis plays an indispensable role in machine learning and data mining. Learning a good data representation is crucial for clustering algorithms. Recently, deep clustering (DC), ...