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Blind deblurring attempts to recover the latent sharp image from a blurred one. Such task is a well-known ill-posed inverse problem and is therefore usually solved as a posteriori probability estimation, incorporating prior information on natural images. In this paper, we propose a general blind noisy deblurring model based on hyper Laplacian (HL) in gradient domain and kernel spectra prior. This...
To improve the startup speed of the embedded devices has a very important significance for application and development of embedded Linux systems. The paper analysed the startup process of embedded Linux systems, based on the method of accelerate way of modern system, proposed a new way to accelerate the startup speed of embedded Linux system, and applied this method to the specific embedded board...
For an N-class problem, the decision directed acyclic support vector machines (DAG-SVM) construct N(N-1)/2 classifiers, one for each pair of classes. But the generalization performance of the original DAG-SVM depends a lot on the nodes sequence of the directed acyclic graph. To get a good generalization performance, genetic algorithm is used to permute searching nodes in a DAG. For any test sample,...
Directed Acyclic Graph-Support Vector Machine (DAG-SVM) is a novel algorithm for multi-class classification. For an N-class problem, it constructs N(N-1)/2 classifiers, one for each pair of classes. Based on SVM decision function, an efficient data structure is used to express the decision node in the graph and an improved decision algorithm is used to find the class of each test sample. This new...
To be represented in tabular form and graphical format in ship electronic navigation system, printing tidal material must be processed into textual information, which is completed by an automatic tide table recognition module consisting of a feature extractor and a classifier. In feature extraction, a new wavelet part grid feature is defined based on wavelet's directive characteristics. In classification...
Since hyper-sphere SVM treat all samples equally, its performance is lower when distribution of the training examples is uneven. How to eliminate the influence of the uneven class sizes is important for the resulting classifier. To solve this problem, we present a new weighted hyper-sphere SVM based on the analysis of performance influence caused by the class size. Experimental results show that our...
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