Abstract: Safe flight in dynamic environments requires unmanned aerial vehicles (UAVs) to make effective decisions when navigating cluttered spaces with moving obstacles. Traditional approaches often ...

Abstract: The trajectory tracking plays a vital role in unmanned driving technology. Although traditional control schemes may yield satisfactory outcomes in dealing with simple linear tasks, they may ...

Abstract: In this issue, “Best of the Web” presents the modified National Institute of Standards and Technology (MNIST) resources, consisting of a collection of handwritten digit images used ...

Abstract: Threshold signatures are a helpful cryptographic primitive to ensure redundancyand distribution of trust for a secret signing key. In this article, we introduce the concept ofthreshold ...

Abstract: Accurate semantic segmentation of remote sensing data plays a crucial role in the success of geoscience research and applications. Recently, multimodal fusion-based segmentation models have ...

Abstract: In several applications the information is naturally represented by graphs. Traditional approaches cope with graphical data structures using a preprocessing phase which transforms the graphs ...

Abstract: There are still various challenges in remote sensing semantic segmentation due to objects diversity and complexity. Transformer-based models have significant advantages in capturing global ...

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: 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: The misalignment between RGB and thermal images significantly impairs RGB-Thermal semantic segmentation accuracy. Current non-end-to-end methods treat RGB-Thermal registration independently ...

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: Evolutionary Reinforcement Learning (ERL), which integrates Evolutionary Algorithms (EAs) and Reinforcement Learning (RL) for optimization, has demonstrated remarkable performance ...