Micromanipulation robot is a system which often does some precise manipulations in micro scale space, such as centimeter or millimeter level space, in which micro visual servo system plays a very important role. In vi...
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In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for im...
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ISBN:
(纸本)9780819469519
In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for image fusion. Each image from different sensors could be decomposed into a low frequency image and a series of high frequency images of different directions by multi-sacle NSCT. For low and high frequency images, they are fused based on local-contrast enhancement and definition respectively. Finally, fused image is reconstructed from low and high frequency fused images. Experiment demonstrates that NSCT could preserve edge significantly and the fusion rule based on region segmentation performances well in local-contrast enhancement.
It is necessary to study the radiation characteristic of metal solid objects for millimeter wave passive guidance. On the basis of discussing the grounded theory, the antenna temperature contrast formula of metal soli...
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ISBN:
(纸本)0780384016
It is necessary to study the radiation characteristic of metal solid objects for millimeter wave passive guidance. On the basis of discussing the grounded theory, the antenna temperature contrast formula of metal solid objects is presented. Furthermore equivalent radiometric section coefficient based on scale-shrinking measuring theory is proposed in favor of engineering applications. The 8 mm theoretical calculation and actual measurement are mostly below 1K. So, equivalent radiometric section coefficient gives a virtual way for engineering measurement of metal solid objects.
Aircraft final assembly line(AFAL)involves thousands of processes that must be completed before ***,the heavy reliance on manual labor in most assembly processes affects the quality and prolongs the delivery *** the a...
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Aircraft final assembly line(AFAL)involves thousands of processes that must be completed before ***,the heavy reliance on manual labor in most assembly processes affects the quality and prolongs the delivery *** the advent of artificial intelligence of things(AIoT)technologies has introduced advancements in certain AFAL scenarios,systematically enhancing the intelligence level of the AFAL and promoting the widespread deployment of artificial intelligence(AI)technologies remain significant *** address these challenges,we propose the intelligent and collaborative aircraft assembly(ICAA)framework,which integrates AI technologies within a cloud-edge-terminal *** ICAA framework is designed to support AI-enabled applications in the AFAL,with the goal of improving assembly efficiency at both individual and multiple process *** analyze specific demands across various assembly scenarios and introduce corresponding AI technologies to meet these *** three-tier ICAA framework consists of the assembly field,edge data platform,and assembly cloud platform,facilitating the collection of heterogeneous terminal data and the deployment of AI *** framework enhances assembly efficiency by reducing reliance on manual labor for individual processes and fostering collaboration across multiple *** provide detailed descriptions of how AI functions at each level of the ***,we apply the ICAA framework to a real AFAL,focusing explicitly on the flight control system testing *** practical implementation demonstrates the effectiveness of the framework in improving assembly efficiency and promoting the adoption of AIoT technologies.
The analytical algorithm of program quaternion is studied, aiming at the problem of the arbitrary spacecraft attitude-adjusting control. It also provides the analytical constructor method of the program quaternion for...
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Scoring of sleep stages plays an important role in the diagnosis of sleep-related diseases. Scoring by visual inspection is time-consuming and heavily depends on the experience of experts. Thus, there is an urgent nee...
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Scoring of sleep stages plays an important role in the diagnosis of sleep-related diseases. Scoring by visual inspection is time-consuming and heavily depends on the experience of experts. Thus, there is an urgent need for an automatic sleep stage classification system. This paper proposes a novel compact convolutional neural network (C-CNN) using only single-channel EEG signal. Compared with traditional machine learning approaches based on hand-engineered features, our approach provides an end-to-end solution that requires almost no prior knowledge and preprocessing while achieving better performance. Experiments on the expanded Sleep-EDF database verified its effectiveness and efficiency. In addition, we notice the issue of class imbalance in sleep stages, and a class-imbalance metric, the balanced classification accuracy (BCA), is introduced. At the cost of a little drop in accuracy, which is still higher than existing classification methods, the introduction of class-imbalance weights can significantly increase the BCA metric and result in a higher recall for each sleep stage. This paper also proposes a recurrent neural network based on the attention mechanism and bidirectional long short-term memory (LSTM), which provides better performance than C-CNN but requires more training time.
National-scale transportation systems are critical infrastructures to ensure the normal operation of the nation and offer essential services to modern societies. And they face a constant barrage of external stresses o...
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With a concern about the missile attitude control system, this paper attempts to solve the online calculation method of the coefficient of the small deviation equation, on which a LFT-based LPV model of the missile at...
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Nonnegative matrix factorization (NMF) is an increasingly popular technique for data processing and analysis. For an incomplete data matrix, the weighted nonnegative matrix factorization (WNMF) is employed to decompos...
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Nonnegative matrix factorization (NMF) is an increasingly popular technique for data processing and analysis. For an incomplete data matrix, the weighted nonnegative matrix factorization (WNMF) is employed to decompose it. But the searching step size in WNMF is not optimal along the given searching direction. This paper studies the incomplete nonnegative matrix factorization (INMF) and proposes an accelerated algorithm. First, INMF is transformed into solving alternatively two nonnegative least squares (NNLS) problems. For each NNLS problem, the exact step size is chosen along the searching direction. Then, the complexity of NNLS problems is analyzed. Finally, experimental results show that the proposed method outperforms WNMF.
An accurate prediction of landslide displacement is challenging and of great interest to governments and researchers. In order to reduce the risk of selecting the types of influencing factors and artificial neural net...
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