Abstract: Unmanned Aerial Vehicles (UAVs) rely on satellite systems for stable positioning. However, due to limited satellite coverage or communication disruptions, UAVs may lose signals for ...

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: 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: It is an essential task to accurately diagnose cancer subtypes in computational pathology for personalized cancer treatment. Recent studies have indicated that the combination of multimodal ...

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: Recent studies have shown that synchronized ground-based positioning systems, such as pseudolites, can achieve decimeter-level to centimeter-level positioning. However, highly precise time ...

Abstract: The rapid advancements in wireless technologies have led to numerous research studies that provide evidence of the successful utilization of wireless signals, particularly, WiFi signals for ...

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: 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: The paddy agronomy in the Asia-pacific region has gained a prominent role in connection with the major rice production area in over the decades. The research aims to investigate the aerial ...

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), ...

Abstract: In smart communities, social media allowed users easy access to multimedia content. With recent advancements in computer vision and natural language processing, machine learning (ML), and ...