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Description: The ICA/BSS algorithms are pure mathematical formulas, powerful, but rather mechanical procedures: There is not very much left for the user to do after the machinery has been optimally implemented. The successful and efficient use of the ICALAB strongly depends on a priori knowledge, common sense and appropriate use of the preprocessing and postprocessing tools. In other words, it is preprocessing of data and postprocessing of models where expertise is truly ne-Instruction :
The ICA/BSS algorithms are pure mathematical formulas, powerful, but rather mechanical procedures: There is not very much left for the user to do after the machinery has been optimally implemented. The successful and efficient use of the ICALAB strongly depends on a priori knowledge, common sense and appropriate use of the preprocessing and postprocessing tools. In other words, it is preprocessing of data and postprocessing of models where expertise is truly needed.
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Size: 12276376 |
Author: 孙占全 |
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Description: 用costas环检测淹没在噪声和未知任何先验参数的正弦信号检测-with Costas Loop Detection drowned in the noise and any a priori unknown parameters of sinusoidal signal detection
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Size: 1980 |
Author: 邓德鑫 |
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Description: 文章介绍了利用车牌的纹理特征和区域形状特征检测车牌区域情况。为提高区域检
测的正确性, 利用新的改进的主动轮廓模型, 利用先验知识确定精确的车牌边界。在精确的车牌区
域中切割出车牌中的单个字符, 最后利用支持矢量机对字符进行分类识别。
汤志勇 杨晨晖 王炳波
(厦门大学 厦门361005)-article describes the use of the plates texture characteristics and the shape feature detection plates regional situations. To improve the accuracy of detection region, the use of new initiatives to improve the contour model, the use of a priori knowledge to determine the exact license plate boundary. The exact number plates region cut out plates of a single character, the final use of support vector machines for character recognition and classification. Tang Zhiyong Yang Chen-hui Wangbingbei (Xiamen University, Xiamen 361005)
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Author: adnsid |
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Description: 语音信号的盲分离，是一个很好的在没有先验知识的情况下的分离程序！-voice signals in the blind separation is a good in the absence of a priori knowledge of the separation procedure!
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Size: 3056 |
Author: 郭文强 |
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Description: 计算高斯混合模型先验概率和后验概率的程序，采用大矩阵运算，大大提高了运行速度。-Gaussian mixture model calculated a priori probability and the probability of post-mortem procedures, using a large matrix computation, greatly improved speed.
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Size: 1758 |
Author: gqy |
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Description: 在源码实现的研究过程中将采取基于水平集方法的几何活动轮廓模型如测地轮廓模型或Mumford-shah模型与其他的分割方法的结合。针对具体的图像可以将一些先验知识（灰度和形状信息）加入到算法中-source realized in the course of the study will be taken based on the level set method of the geometric active contour models such as the geodesic contours Die Mumford - or-shah model and the other a combination of segmentation. Specific image may be some a priori knowledge (gray and shape information) to join algorithm
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Size: 55877 |
Author: 牛牛 |
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Description: 聚类分析技术有着广泛应用.因为在对图像进行聚类分析时,通常缺少可资利用的先验知识,所以需要采用无监督的聚类算法.为了适应图像检索的需要,提出了一种新型的无监督聚类方法,即根据离群点信息来自动确定聚类算法的终止时机.此方法还弥补了现有聚类算法在离群点识别、使用上的缺欠.为验证其可行性,用其改进了CURE和ROCK两个经典算法.实验表明,改进后的两个算法都能自动终止,并能取得优于以往的聚类效果. -clustering analysis techniques have wide application. In the image clustering analysis, usually available to the lack of a priori knowledge, Therefore, the need for unsupervised clustering algorithm. To meet the needs of image retrieval, propose a novel unsupervised clustering method, That is, according to information outliers automatically clustering algorithm to determine the time of termination. This method also makes up for in the existing clustering algorithm outliers identification, the use of the shortcomings. To test its feasibility. use its improved CURE ROCK and two classical algorithm. Experiments show that The two improved algorithm can automatically terminated and can be made better than the previous clustering effect.
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Size: 1467 |
Author: 陈一 |
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Description: 一种车牌字符分割方法，属于图象处理技术领域，涉及车牌自动识别技术。采用拉普拉斯变换、区域生长和车牌先验知识相结合的方法-a license plate characters segmentation method, is the field of image processing technology, involving the installation of the Automatic Identification Technology. Using Laplace transform, regional growth and a priori knowledge plates combination of
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Author: mabin |
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Description: Apriori算法的JAVA实现A priori算法的JAVA实现
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Size: 3351 |
Author: hydra |
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Description: The ICA/BSS algorithms are pure mathematical formulas, powerful, but rather mechanical procedures: There is not very much left for the user to do after the machinery has been optimally implemented. The successful and efficient use of the ICALAB strongly depends on a priori knowledge, common sense and appropriate use of the preprocessing and postprocessing tools. In other words, it is preprocessing of data and postprocessing of models where expertise is truly ne-Instruction :
The ICA/BSS algorithms are pure mathematical formulas, powerful, but rather mechanical procedures: There is not very much left for the user to do after the machinery has been optimally implemented. The successful and efficient use of the ICALAB strongly depends on a priori knowledge, common sense and appropriate use of the preprocessing and postprocessing tools. In other words, it is preprocessing of data and postprocessing of models where expertise is truly needed.
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Size: 12275712 |
Author: 孙占全 |
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Description: Apriori算法的JAVA实现A priori算法的JAVA实现-Apriori algorithm JAVA realize A priori algorithm realize JAVA
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Size: 3072 |
Author: |
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Description: 基于Snake 模型的图像分割技术是近年来图像处理领域的研究热点之一。Snake 模型承载上层先验知识并融合
了图像的底层特征,针对医学图像的特殊性,能有效地应用于医学图像的分割中。本文对各种基于Snake 模型的改进算法和
进化模型进行了研究,并重点梳理了最新的研究成果,以利于把握基于Snake 模型的医学图像分割方法的脉络和发展方向。-Snake model based on image segmentation image processing technology in recent years one of the hot areas of research. Snake model bearing a priori knowledge of the upper and bottom of the convergence of image features, for the specificity of medical images can be effectively applied to medical image segmentation. In this paper, model-based Snake improved algorithm and evolutionary models were studied and focused on combing the latest research results, in order to grasp the Snake model based on medical image segmentation method of context and direction of development.
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Size: 476160 |
Author: 赵希成 |
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Description: apriori算法的java代码，APRRORI算法使用频繁项性质的先验知识，逐层搜索迭代，用K-项集产生(K+1)-项集。APRRORI算法的一个显著特点是:利用APRIORI性质，压缩了频繁项集，提高了算法的效率。
-apriori algorithm java code, APRRORI algorithm uses the a priori nature of frequent itemsets knowledge, step by step iterative search using K-itemsets generated (K+ 1)- itemsets. APRRORI algorithm A significant feature is: the nature of the use of APRIORI, compression of the frequent itemsets, improve the efficiency of the algorithm.
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Size: 21504 |
Author: xinyuanwo |
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Description: 高光谱图像的顶点成分分析，在没有先验知识背景下，提取图像中的端元-Hyperspectral Image vertex component analysis, in the absence of a priori knowledge of background, the extracted image Endmember
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Size: 1024 |
Author: yudongjun |
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Description: Wiener filter based on tracking a priori SNR usingDecision-Directed
method, proposed by Scalart et al 96.-Wiener filter based on tracking a priori SNR usingDecision-Directed method, proposed by Scalart et al 96.
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Size: 3072 |
Author: Ming |
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Description: Maximum a priori L-values
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Size: 1024 |
Author: Imran |
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Description: 该算法是经典的信噪比估计算法——最大似然估计算法，利用接收信道的先验概率密度函数，ML法能够很好的估计信号的信噪比-The algorithm is a classic signal to noise ratio estimation algorithm- maximum likelihood estimation algorithm, using the a priori receiver channel probability density function, ML method can be a very good signal to noise ratio is estimated
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Size: 1024 |
Author: 贾小勇 |
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Description: Apriori算法【l】：1994年由R．Agrawal等人提出来的Apriori算法是
关联规则挖掘的一个经典算法，后来的许多算法都是基于该算法的思想。算
法的名称来源于在算法中应用了频繁项集的先验知识，即：一个频繁项集的
任一非空子集必定是频繁项集；因此只要某一项集是非频繁的，则其超集就
无须再检验。-Apriori algorithm】 【l: 1994 by R. Agrawal et al to the Apriori algorithm is a classical association rule mining algorithm, and later many of the algorithms are based on the idea of the algorithm. The name comes from the algorithm applied in the algorithm a priori knowledge of frequent item sets, ie: any of a frequent itemset must be a non-empty subset of frequent item sets so long as a particular set of non-frequent, its superset to no longer need to test.
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Size: 205824 |
Author: plairstar |
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Description: Wiener filter based on tracking a priori SNR usingDecision-Directed
method, proposed by Scalart et al 96. In this method it is assumed that
SNRpost=SNRprior +1. based on this the Wiener Filter can be adapted to a
model like Ephraims model in which we have a gain function which is a
function of a priori SNR and a priori SNR is being tracked using Decision
Directed method.
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Size: 3072 |
Author: yfliao |
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Description: 暗原色先验的去雾算法，何凯明的英文文章，很值得参考-Dark colors priori
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Size: 6492160 |
Author: yangrongrong |
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