A towfish is a passive underwater vehicle that is towed behind a surface vessel. The towfish is often designed to be symmetric from all directions primarily to achieve balanced hydrodynamic behaviour and foreseeable m...
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Model predictive path-following control (MPFC) considers geometric reference paths in output spaces without pre-assigned timing information. It combines trajectory generation and tracking into one receding-horizon opt...
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Aiming at the problem that the control station cannot accurately intervene in real time and when encountering unforeseen threats such as air-to-air/surface-to-air missile attacks in air combat missions, research gener...
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As remote sensing technology continues to advance, the accuracy and quantity of remote sensing images have significantly improved. The generation of a vast amount of available data has facilitated the widespread appli...
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ISBN:
(数字)9781510675001
ISBN:
(纸本)9781510674998
As remote sensing technology continues to advance, the accuracy and quantity of remote sensing images have significantly improved. The generation of a vast amount of available data has facilitated the widespread application of various deep learning methods in the field of remote sensing data processing, such as object detection, semantic segmentation, and change detection. In the aforementioned tasks, Change detection is used to identify alterations occurring on the Earth's surface by utilizing remote sensing (RS) data. In recent years, deep learning based methods have exhibited significantly superior performance compared to traditional change detection techniques. The fundamental strategy enabling these advancements involves extracting appropriate deep learning features from input remote sensing images through various backbone networks such as VGG, ResNet, DenseNet etc. Nevertheless, the features extracted by the aforementioned backbone networks may not fully cater to the specific requirements of remote sensing image change detection tasks. Consequently, our goal is to explore the influence of features extracted by different backbone networks on change detection tasks and introduce a specialized backbone network tailored for change detection. This endeavor aims to produce features that are better suited for the of change detection. The experimental results indicate that our specifically designed feature extraction network for remote sensing image change detection outperforms traditional networks in extracting task-specific features. These features are better suited for subsequent decoder modules, enhancing the generation of image-based change detection results. At the same time, we found that when using general backbone networks for change detection, ResNet achieves the highest metric accuracy, while DenseNet has the lowest memory usage and the fastest training and testing speed. Depending on the specific task, we can choose the appropriate backbone network as need
A six-degree-of-freedom (6DOF) control scheme is proposed for the glide phase of hypersonic vehicle. Based on hypersonic vehicle motion and engagement model, the 3D integrated guidance and control (IGC) model is const...
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The huge state space and varying action space will make the decision-making be a grand challenge for reinforcement learning. To address this problem, we propose a multi-agent hierarchical decision optimization algorit...
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A novel framework in multi-agent system networks is introduced and analyzed in this article, namely coupled output synchronization over directed graph topologies. Under assumptions of a rooted spanning tree, we design...
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In this paper, we address the safety verification problem of switched linear dynamical systems under arbitrary switching via barrier functions. Our approach is based on a notion of path-complete barrier functions, whi...
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Using hydrogen as a fuel in spark ignition (SI) internal combustion engines offers an environmentally friendly alternative to fossil fuels, while retaining many benefits of conventional powertrains. Even though the hy...
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This article presents a novel framework for the robust controller synthesis problem in discrete-time systems using dynamic Integral Quadratic Constraints (IQCs). We present an algorithm to minimize closed-loop perform...
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