intelligent industrial manufacturing heavily relies on structured knowledge. Named Entity Recognition (NER), an essential technique for extracting structured knowledge from text, has garnered significant research inte...
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Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years. Over the past two decades, we have seen a rapid technological evolution of ob...
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Most contemporary supervised Remote Sensing (RS) image Change Detection (CD) approaches are customized for equal-resolution bitemporal images. Real-world applications raise the need for cross-resolution change detecti...
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Monitoring changes in the Earth’s surface is crucial for understanding natural processes and human impacts, necessitating precise and comprehensive interpretation methodologies. Remote sensing satellite imagery offer...
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This paper addresses the global consensus problem for multi-input multi-output saturated systems within a sampled-data framework, aiming to advance global consensus, manage heterogeneous actuator saturation across com...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
This paper addresses the global consensus problem for multi-input multi-output saturated systems within a sampled-data framework, aiming to advance global consensus, manage heterogeneous actuator saturation across components, and preserve distributed characteristics by using sampled-data feedback. We propose a distributed control algorithm that incorporates a redesigned saturation function, represented as decentralized dynamic saturation levels. These levels for each agent’s dimensions are autonomously updated through an adaptive strategy, which mitigates heterogeneous saturation by carefully selecting constant and time-varying saturation parameters in it. Lyapunov analysis proves that global consensus can be achieved under the proposed control law, provided the sampling periods of all agents remain below a calculated threshold. An example is given to demonstrate the effectiveness of this approach.
The electric vehicle (EV) and electric vehicle charging station (EVCS) have been widely deployed with the development of large-scale transportation electrifications. However, since charging behaviors of EVs show large...
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Underwater images are often influenced by color casts, low contrast, and blurred details. We observe that images taken in natural settings typically have similar histograms across color channels, while underwater imag...
Underwater images are often influenced by color casts, low contrast, and blurred details. We observe that images taken in natural settings typically have similar histograms across color channels, while underwater images do not. To improve the natural appearance of an underwater image, it is critical to improve the histogram similarity across its color channels. To address this problem, we develop a histogram similarity-oriented color compensation method that corrects color casts by improving the histogram similarity across color channels in the underwater image. In addition, we apply the multiple attribute adjustment method, including max-min intensity stretching, luminance map-guided weighting, and high-frequency edge mask fusion, to enhance contrast, saturation, and sharpness, effectively addressing problems of low contrast and blurred details and eventually enhancing the overall appearance of underwater images. Particularly, the method proposed in this work is not based on deep learning, but it effectively enhances a single underwater image. Comprehensive empirical assessments demonstrated that this method exceeds state-of-the-art underwater image enhancement techniques. To facilitate public assessment, we made our reproducible code available at https://***/wanghaoupc/UIE_HS2CM2A.
In this paper, we revisit the interval observer design problem of harmonic oscillator system with unknown but bounded external disturbance and measurement noise. With the bounding information of the external disturban...
In this paper, we revisit the interval observer design problem of harmonic oscillator system with unknown but bounded external disturbance and measurement noise. With the bounding information of the external disturbance and measurement noise, a high-gain interval observer is firstly defined and constructed for the harmonic oscillator system to realize the interval estimation on the state and the robust control of the system. Then, a switched high-gain interval observer is proposed to reduce the influence of the measurement noise for a tighter interval width on the state estimation. Finally, some numerical simulations are given to verify the theoretical results.
A novel evolutionary route planner for aircraft is proposed in this paper. In the new planner, individual candidates are evaluated with respect to the workspace, thus the computation of the configuration space is not ...
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A novel evolutionary route planner for aircraft is proposed in this paper. In the new planner, individual candidates are evaluated with respect to the workspace, thus the computation of the configuration space is not required. By using problem-specific chromosome structure and genetic operators, the routes are generated in real time,with different mission constraints such as minimum route leg length and flying altitude, maximum turning angle, maximum climbing/diving angle and route distance constraint taken into account.
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