Abstract: Remote sensing images (RSIs) spatiotemporal fusion (STF) make a significant contribution to acquisition of RSIs sequence with simultaneously high temporal and spatial resolution, which ...

Abstract: The penetration of distributed energy resources in electrical grids has been steadily increasing in an effort to reduce greenhouse gas emissions. Inverters, as interfaces between distributed ...

Abstract: In the context of rapidly growing city road networks, understanding complex traffic patterns and implementing effective safety monitoring through advanced Transportation Cyber-Physical ...

Abstract: With the rapid advancement of wearable devices and Internet of Things (IoT) technologies, sensor data generated by edge devices has surged. This data is crucial for advancing IoT ...

Abstract: Existing visual deep learning paradigms, which are based on labels, struggle to capture the intricate interrelationships between farmland and its surrounding environment and fail to account ...

Abstract: Agentic AI, an emerging paradigm in artificial intelligence, refers to autonomous systems designed to pursue complex goals with minimal human intervention. Unlike traditional AI, which ...

Abstract: In the field of Internet of Things (IoT), uncrewed aerial vehicle (UAV) swarms are widely used to assist IoT communication due to their simple deployment, high mobility and high cost ...

Abstract: Semantic segmentation of remote sensing images (RSIs) is vital for numerous geospatial applications, including land-use mapping, urban planning, and environmental monitoring. Traditional ...

Abstract: Computer-aided pathology diagnosis based on whole slide images, which is often formulated as a weakly supervised multiple instance learning (MIL) paradigm. Current approaches generally ...

Abstract: Measurements of the equivalent parallel conductance of metal-insulator-semiconductor (MIS) capacitors are shown to give more detailed and accurate information about interface states than ...

Abstract: In the realm of computer vision (CV), balancing speed and accuracy remains a significant challenge. Recent efforts have focused on developing lightweight networks that optimize computational ...

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 ...