Abstract: Multiview subspace clustering aims to discover the inherent structure of data by fusing multiple views of complementary information. Most existing methods first extract multiple types of ...

Abstract: Convolutional neural networks (CNNs) and Transformers have made impressive progress in the field of remote sensing change detection (CD). However, both architectures have inherent ...

Abstract: This work proposes an incremental Generalized Iterative Closest Point (GICP) based tightly-coupled LiDAR-inertial odometry (LIO), iG-LIO, which integrates the GICP constraints and inertial ...

Abstract: Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise information for diverse downstream applications. Recent development of the segment anything model ...

Abstract: Although deep reinforcement learning (DRL) methods are promising for making behavioral decisions in autonomous vehicles (AVs), their low training efficiency and difficulty to adapt to ...

Abstract: This letter presents a synthesis method for fractional-order filters, which transforms the conventional discrete filter order into a continuous number. The method introduces an additional ...

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: Orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) is promising for future sixth-generation mobile communication systems. For OFDM-based ISAC ...

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: 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: 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 ...

Abstract: Detecting infrared small targets quickly and accurately in complex backgrounds has always been a challenging task. Data-driven methods have achieved good results because of their powerful ...