A novel method of speckle suppression for SAR image based on the curvelet transform is presented. A Bayesian shrinkage factor is derived to shrink the curvelet coefficients, then the mean filter and the nonlinear anis...
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Planning detailed military course of action (COA) is very complex and time consuming. In this paper, a method based on multi-agent evolutionary algorithm was presented to solve COA' resource management and schedul...
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In this paper, we present a novel approach for detecting the changed regions caused by flooding events in multi-temporal SAR images. And the proposed method concludes two parts: 1) constructing difference image (DI) b...
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In this paper, an improved contour detection method based on level set and watershed transform is proposed. It is performed on coarse-to-fine approach: 1) primary contours detected by using level set evolution;2) accu...
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Synthetic aperture radar (SAR) data collections can cover large areas at high resolution, generating massive amounts of data. Many existed transform-based compression techniques can effectively reduce the costs of sto...
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Owing to the weaknesses of existing correlation detection methods in digital fingerprint matching, such as difficult to determine the threshold and low matching accuracy rate, a method proposed in digital fingerprint ...
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Based on the concepts and principles of quantum computing, a quantum-inspired evolutionary algorithm for data clustering (QECA) is proposed in this paper. And a novel distance measurement index called manifold distanc...
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ISBN:
(纸本)9781605583266
Based on the concepts and principles of quantum computing, a quantum-inspired evolutionary algorithm for data clustering (QECA) is proposed in this paper. And a novel distance measurement index called manifold distance is introduced. These attribute data are the main source of clustering problem, due to its complex distribution, most clustering algorithms available are only suitable for these types of characteristic data. In this study, a new algorithm which can deal with these data with manifold distribution is more effective. The main motives of using QECA consist in searching for appropriate cluster center so that a similarity metric of clusters are optimized more quickly and effectively. The superiority of QECA over fuzzy c-means (FCM) algorithm and immune evolutionary clustering algorithm (IECA) is extensively demonstrated in our experiments. Copyright 2009 ACM.
In this paper, a semi-fragile watermark solution based on quantization index modulation in the wavelet region was proposed. The algorithm employs a compressed halftoned binary image as watermark and embeds it in the w...
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Inspired by the principle of gene transposon proposed by Barbara McClintock, a new immune computing algorithm for clustering multi-class data sets named as Gene Transposition based Clone Selection Algorithm (GTCSA) is...
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ISBN:
(纸本)9781605583259
Inspired by the principle of gene transposon proposed by Barbara McClintock, a new immune computing algorithm for clustering multi-class data sets named as Gene Transposition based Clone Selection Algorithm (GTCSA) is proposed in this paper, The proposed algorithm does not require a prior knowledge of the numbers of clustering;an improved variant of the clonal selection algorithm has been used to determine the number of clusters as well as to refine the cluster center. a novel operator called antibody transposon is introduced to the framework of clonal selection algorithm which can realize to find the optimal number of cluster automatically. The proposed method has been extensively compared with Variable-string-length Genetic Algorithm(VGA)based clustering techniques over a test suit of several real life data sets and synthetic data sets. The results of experiments indicate the superiority of the GTCSA over VGA on stability and convergence rate, when clustering multi-class data sets. Copyright 2009 ACM.
A novel synthetic aperture radar (SAR) automatic target recognition (ATR) approach based on Curvelet Transform is proposed. However, the existing approaches can not extract the more effective feature. In this paper, o...
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