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排序方式： 共有762条查询结果，搜索用时 15 毫秒
51.
一种基于Laplacian矩阵的图像匹配算法 总被引：2，自引：0，他引：2
文章提出了一种基于Laplacian矩阵的图像特征匹配算法。首先分别构造两幅图像特征点集的Laplacian矩阵,并对这两个矩阵进行奇异值分解(SVD),然后利用分解的结果构造出一个反应特征点之间匹配程度的关系矩阵,最后根据关系矩阵实现两幅图像的特征点匹配。大量实验结果表明,该文所提出的算法具有较高的匹配精度。 相似文献
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Alain BrettoAuthor Vitae Hocine CherifiAuthor Vitae Driss AboutajdineAuthor Vitae 《Pattern recognition》2002,35(3):651-658
Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to segmentation, edge detection and noise cancellation. 相似文献
54.
根据热平衡理论建立了启动过程中瞬态热平衡微分方程，并对该微分方程进行了一系列数理分析，得出了供回水温度随时间的变化规律，并经实验证实，该规律与实际状态是一致的。 相似文献
55.
Knowledge distillation has become a key technique for making smart and light-weight networks through model compression and transfer learning. Unlike previous methods that applied knowledge distillation to the classification task, we propose to exploit the decomposition-and-replacement based distillation scheme for depth estimation from a single RGB color image. To do this, Laplacian pyramid-based knowledge distillation is firstly presented in this paper. The key idea of the proposed method is to transfer the rich knowledge of the scene depth, which is well encoded through the teacher network, to the student network in a structured way by decomposing it into the global context and local details. This is fairly desirable for the student network to restore the depth layout more accurately with limited resources. Moreover, we also propose a new guidance concept for knowledge distillation, so-called ReplaceBlock, which replaces blocks randomly selected in the decoded feature of the student network with those of the teacher network. Our ReplaceBlock gives a smoothing effect in learning the feature distribution of the teacher network by considering the spatial contiguity in the feature space. This process is also helpful to clearly restore the depth layout without the significant computational cost. Based on various experimental results on benchmark datasets, the effectiveness of our distillation scheme for monocular depth estimation is demonstrated in details. The code and model are publicly available at : https://github.com/tjqansthd/Lap_Rep_KD_Depth. 相似文献
56.
Marc Josien Yves‐Patrick Pellegrini Frédéric Legoll Claude Le Bris 《International journal for numerical methods in engineering》2018,113(12):1827-1850
This work addresses the numerical approximation of solutions to a dimensionless form of the Weertman equation, which models a steadily moving dislocation and is an important extension (with advection term) of the celebrated Peierls‐Nabarro equation for a static dislocation. It belongs to the class of nonlinear reaction‐advection‐diffusion integro‐differential equations with Cauchy‐type kernel, thus involving an integration over an unbounded domain. In the Weertman problem, the unknowns are the shape of the core of the dislocation and the dislocation velocity. The proposed numerical method rests on a time‐dependent formulation that admits the Weertman equation as its long‐time limit. Key features are (1) time iterations are conducted by means of a new, robust, and inexpensive Preconditioned Collocation Scheme in the Fourier domain, which allows for explicit time evolution but amounts to implicit time integration, thus allowing for large time steps; (2) as the integration over the unbounded domain induces a solution with slowly decaying tails of important influence on the overall dislocation shape, the action of the operators at play is evaluated with exact asymptotic estimates of the tails, combined with discrete Fourier transform operations on a finite computational box of size L; (3) a specific device is developed to compute the moving solution in a comoving frame, to minimize the effects of the finite‐box approximation. Applications illustrate the efficiency of the approach for different types of nonlinearities, with systematic assessment of numerical errors. Converged numerical results are found insensitive to the time step, and scaling laws for the combined dependence of the numerical error with respect to L and to the spatial step size are obtained. The method proves fast and accurate and could be applied to a wide variety of equations with moving fronts as solutions; notably, Weertman‐type equations with the Cauchy‐type kernel replaced by a fractional Laplacian. 相似文献
57.
In a cloud marketplace, the existence of wide range of Cloud Service Providers (CSPs) makes it hard for the Cloud Users (CUs) to find an appropriate CSP based on their requirements. The design of a suitable service selection framework helps the users in the selection of a suitable CSP, while motivating the CSPs to satisfy the assured Service Level Agreement (SLA) and enhance the Quality of Service (QoS). Existing service selection models employ random assignment of weights to the QoS attributes, replacement of missing data by random values, etc. which results in an inaccurate ranking of the CSPs. Moreover, these models have high computational overhead. In this study, a novel cloud service selection architecture, Hypergraph based Computational Model (HGCM) and Minimum Distance-Helly Property (MDHP) algorithm have been proposed for ranking the cloud service providers. Helly property of the hypergraph had been used to assign weights to the attributes and reduce the complexity of the ranking model, while arithmetic residue and Expectation–Maximization (EM) algorithms were used to impute missing values. Experimental results provided by MDHP under different case studies (dataset used by various research communities and synthetic dataset) confirms the ranking algorithm to be scalable and computationally attractive. 相似文献
58.
Thresholding technique is one of the most imperative practices to accomplish image segmentation. In this paper, a novel thresholding algorithm based on 3D Otsu and multi-scale image representation is proposed for medical image segmentation. Considering the high time complexity of 3D Otsu algorithm, an acceleration variant is invented using dimension decomposition rule. In order to reduce the effects of noises and weak edges, multi-scale image representation is brought into the segmentation algorithm. The whole segmentation algorithm is designed as an iteration procedure. In each iteration, the image is segmented by the efficient 3D Otsu, and then it is filtered by a fast local Laplacian filtering to get a smoothed image which will be input into the next iteration. Finally, the segmentation results are pooled to get a final segmentation using majority voting rules. The attractive features of the algorithm are that its segmentation results are stable, it is robust to noises and it holds for both bi-level and multi-level thresholding cases. Experiments on medical MR brain images are conducted to demonstrate the effectiveness of the proposed method. The experimental results indicate that the proposed algorithm is superior to the other multilevel thresholding algorithms consistently. 相似文献
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