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在Visual C++下实现聚类分析在图像识别中的应用。其中包括模糊聚类，遗传算法聚类分析，层次聚类和动态聚类等算法。可以运行，并有分类的源文件。是不错的研究素材。,In Visual C++ Achieve clustering analysis in image recognition applications. Including fuzzy clustering, genetic algorithm for cluster analysis, hierarchical clusterin
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C均值模糊聚类，适用于图像分类，此为MATLAB 程序代码。-C mean fuzzy clustering for image classification, this is MATLAB code.
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模糊C均值分类，用于图像处理中 很好用的，极力推荐 -Fuzzy C-means classification, used for image processing in a very good use, and strongly recommend
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matlab图像分类分割编程
利用matlab 的fuzzy分类为图像分类编写的matlab程序-image classification segmentation matlab programming
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一种基于形态学的图像增强方法。基于模糊逻辑将二值形态学分级算子推广到灰度图象，研究灰度形态学分级算子。-Morphology-based methods of image enhancement. Will be based on the fuzzy logic classification binary morphological operator to the gray-scale images, gray-scale morphological study operator classif
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模糊c均值聚类算法对遥感图像分类，可自己进行修改-Fuzzy c means clustering algorithm for remote sensing image classification can be modify their
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提出了基于特征融合和模糊核判别分析(FKDA)的面部表情识别方法。首先，从每幅人脸图像中手工定
位34个基准点，作为面部表情图像的几何特征，同时采用Gabor小波变换方法对每幅表情图像进行变换，并提取基
准点处的Gabor小波系数值作为表情图像的Gabor特征；其次，利用典型相关分析技术对几何特征和Gabor特征进
行特征融合，作为表情识别的输人特征；然后，利用模糊核判别分析方法进一步提取表情的鉴别特征；最后，采用最
近邻分类器完成表情的分类识别。通过在JAFFE国际表情数据库和
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聚类分析是多元统计分析的一种，也是无监督模式识别的一个重要分支，在模式分类 图像处理和模糊规则处理等众多领域中获得最广泛的应用。它把一个没有类别标记的样本按照某种准则划分为若干子集，使相似的样本尽可能归于一类，而把不相似的样本划分到不同的类中。硬聚类把每个待识别的对象严格的划分某类中，具有非此即彼的性质，而模糊聚类建立了样本对类别的不确定描述，更能客观的反应客观世界，从而成为聚类分析的主流。-Clustering analysis is a kind of multivariate statis
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：对每一个训练点都定义点模糊度，利用其隶属函数所包含的信息量来确定模糊度，在
此基础上对传统的支持向量机算法进行了改进，提出了基于模糊支持向量机的医学图像分类
技术。-: For each training point of ambiguity points are defined using the membership function to determine the amount of information contained ambiguity, on the basis o
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模糊C均值聚类算法，对图像进行分类，图像处理，多类划分，SAR图像分类-Fuzzy c-means algorithm clustering algorithm, the image classification, image processing, many kinds of division, the SAR image classification
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模糊C均值分类，用于图像处理中 很好用的，极力推荐 -Fuzzy C-means classification, used for image processing in a very good use, and strongly recommend
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图像方面的顶级期刊IEEE Transcations on Image Processing2013年发表的一篇论文 Linear Time Distances Between Fuzzy Sets With Applications to Pattern Matching and Classification -A paper Linear Time Distances Between Fuzzy Sets With Applications to Pattern Matching and
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用模糊增强的方法增加原图像的对比度，以便用于后续分类和分割-Fuzzy enhancement method of increasing the contrast of the original image, so that for subsequent classification and segmentation
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resonance imaging (MRI) data and estimation
of intensity inhomogeneities using fuzzy logic. MRI intensity
inhomogeneities can be attributed to imperfections in the
radio-frequency coils or to problems associated with the acquisition
sequences
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that arises the surface coil array.
This entropy-based method does not require classification and
robustly addresses some problems that are more severe than
those found in brain imaging, including noise, steep bias field,
sensitivity of arter
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vc++开发的图像分类，包括聚类分析，模糊聚类，遗传算法聚类等-vc++ Developed image classification, including cluster analysis, fuzzy clustering, genetic
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模糊C均值分类的实现matlab代码，附上具体图像的处理过程及实现结果(Fuzzy C classification of the realization of matlab code, attached to the specific image processing and implementation results)
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