This paper demonstrates the application of a Lyapunov-Based Model Predictive Control (LBMPC) framework in achieving dynamic positioning (DP) using the Haizhe autonomous underwater vehicle (AUV) as a case study. Moreov...
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Numerous advances and changes have been brought about by digitalization in both our daily lives and the business world. RPA is an all-purpose technology for developing specialized agents, or "bots," that com...
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Semantic segmentation is a basal task and is a typical computer vision problem. Although semantic segmentation is developing rapidly, the speed and accuracy of model segmentation still need to be further improved. For...
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To address the problem of multiple unmanned aerial vehicles (UAVs) cooperatively pursuing and intercepting non-cooperative UAVs in complex environments, we propose a prioritized experience replay multi-agent deep dete...
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Traditional image restoration methods only study the restoration method based on the image itself, without considering the imaging physical process and the radiation characteristics of the object. Therefore, tradition...
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The Nano-Hyperspec spectrometer was used to preprocess Mikania micrantha images, such as geometric correction, image denoising, radiation correction and bad band elimination. The optimal exponential coefficient method...
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In this paper, we propose a system that enables visualization under the situation of scattering media such as fog and smoke by Peplography which is scattering media removal system, on a small GPU machine. Compared to ...
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Ice detection of supercooled large droplets(SLD) is a key technology for ensuring aircraft flight safety. With reference to the advisory circular and combination of the flight scenarios, this paper studies the visual ...
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In the process of detection of rail surface defect with machine vision, crucial step is to denoise and extract feature. Over time, lots of technicist have studied the denoising algorithm and feature recognition algori...
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Contrastive learning methods have attracted considerable attention due to their remarkable success in analyzing graph-structured data. Inspired by the success of contrastive learning, we propose a novel framework for ...
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