Description: 基于AGGLOMERATIVE模型的聚类算法matlab实现-AGGLOMERATIVE model based on the clustering algorithm to achieve Matlab Platform: |
Size: 3072 |
Author:黄风 |
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Description: 基于AGGLOMERATIVE模型的聚类算法matlab实现-AGGLOMERATIVE model based on the clustering algorithm to achieve Matlab Platform: |
Size: 3072 |
Author:黄风 |
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Description: J-linkage 算法，可以用于多体拟合的一种策略，优于Multi-ransac-This paper tackles the problem of fitting multiple instances of a model to data corrupted by noise and outliers. The proposed solution is based on random sampling and conceptual data representation. Each point is represented with the characteristic function of the set of random models that fit the point. A tailored agglomerative clustering, called L-linkage, is used to group points belonging to the same model. The method does not require prior speci?cation of the number of models, nor it necessitate parameters tuning. Experimental results demonstrate thesuperior performances of the algorithm. Platform: |
Size: 275456 |
Author:tomas |
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Description: The VLFeat open source library implements popular computer vision algorithms including SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, and quick shift. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. Platform: |
Size: 1548288 |
Author:fenglei yang |
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Description: VLFeat是一款由Andrea Vedaldi和Brian Fulkerson先生创建的开源图像处理库，都属于机器视觉算法，vlfeat库有C和matlab两种实现，包括了SIFT,MSER, k-means, hierarchical k-means, agglomerative information bottleneck, and quick shift
这个库是C语言写的，效率比较高，支持Windows, Mac OS X, and Linux操作系统。可以在matlab、Shell、C、编译器中配置使用。-VLFeat is offered by the President Andrea Vedaldi and Brian Fulkerson created open source image processing library, are all machine vision algorithms, vlfeat C and matlab library has two implementations, including SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, and quick shift this library is written in C language, more efficient, support for Windows, Mac OS X, and Linux operating systems. In matlab, Shell, C, compiler configurations. Platform: |
Size: 2763776 |
Author:古墓 |
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Description: The VLFeat open source library ，可以用来进行HOG,SIFT等，这是最新版的VLFeat-The VLFeat open source library implements popular computer vision algorithms including HOG, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, and quick shift. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. The latest version of VLFeat is 0.9.17. Platform: |
Size: 14119936 |
Author:飞翔 |
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Description: The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local featurexs extraction and matching. Algorithms incldue Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixes, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. The latest version of VLFeat is 0.9.19. Platform: |
Size: 3018752 |
Author:zhaiyunlong |
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Description: VLFeat是一个跨平台的开源机器视觉库，它囊括了当前流行的机器视觉算法，如SIFT, MSER, HOG, 同时还包含了诸如K-MEANS, Hierarchical K-means的聚类算法。它由C语言编写，并提供了Matlab接口及详细的文档。当前最新的版本是VLFeat 0.9.18 。(The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. The latest version of VLFeat is 0.9.20.) Platform: |
Size: 3016704 |
Author:mgx0225
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