Abstract: Real-time image dehazmg is crucial for applications such as autonomous driving, surveillance, and remote sensing, where haze can significantly reduce visibility. However, many deep learning ...

Abstract: Maxwell's equations are replaced by a set of finite difference equations. It is shown that if one chooses the field points appropriately, the set of finite difference equations is applicable ...

Abstract: Emerging applications, such as autonomous driving and Internet of Things (IoT) services put forward the demand for simultaneous sensing and communication functions in the same system.

Abstract: Metal halide perovskite solar cells (PSCs) have made substantial progress in power conversion efficiency (PCE) and stability in the past decade thanks to the advancements in perovskite ...

Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past ...

Abstract: Large language models (LLMs) have transformed the development of embodied intelligence. By providing a few contextual demonstrations (such as rationales and solution examples) developers can ...

Abstract: With the rapid development of intelligent manufacturing, multi-robot collaborative systems are increasingly integrated into various production processes. In the flexible job shop environment ...

Abstract: Most AI-based channel estimation methods with static environment assumptions suffer from performance degradation due to the distribution shift caused by the varying channel environment. As ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=19 ...

Abstract: This paper proposes a deep reinforcement learning scheme for the primary frequency response of floating offshore wind turbines (FOWTs). Considering the fact that current FOWT simulators ...

Abstract: The miniaturized cage-like metacell is proposed for TE-TM balanced wide-angle transmission using the prior knowledge (PK)-guided generative deep learning (DL) method, enabling a low ...