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: 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: Generative artificial intelligence can make powerful artifacts when used at scale, but developing trust in these artifacts and controlling their creation are essential for user adoption.

Abstract: The traditional Rapidly-exploring Random Tree Star (RRT*) suffers from the low path generation efficiency, numerous invalid exploration points, and unsuitability for navigation in unknown ...

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: 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: Human beings possess a remarkable skill for fine in-hand manipulation, utilizing both intrafinger interactions (in-finger) and finger–environment interactions across a wide range of daily ...

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: 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 ...

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), ...