搜索资源列表
NcutImage_7_AMD64
- Normalized cut code in matlab -Normalized cut code in Matlab
erzhitufenge
- 提出了一种新颖的处理图像视觉聚类问题的方法。与以往关注图像局部特征和局部连续性的方法不同，本文中的方法能够提取关于图像的全局印象。为此，我们将图像分割问题转化为图划分问题并提出了划分中的一种全局判别准则——Ncut (Normalized Cut)。Ncut不仅能够衡量不同聚类之间的相异程度，还能够衡量各聚类内部的相似程度。为求解Ncut 的最优化问题，提出了一种基于广义特征值问题的高效算法，并将此算法应用于静态图像分割，取得了良好的效
Dominantset
- 一种 较新的聚类算法 Dominant-set 的代码，包括聚类算法的代码和测试代码。该算法最大特点 就是基于图理论的 ，相对于Normalized Cut,计算复杂度低很多，况且能自动决定类的个数 -A relatively new clustering algorithm Dominant-set the code, including the clustering algorithm code and test code. Mos
MATLAB
- Normalized Cut Image Segmentation Code -Normalized Cut Image Segmentation Code
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- Normalized Cut Image Segmentation Code
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- Normalized Cut Image Segmentation Code
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- Normalized Cut Image Segmentation Code
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- Normalized Cut Image Segmentation Code
NcutClustering_7
- Data Clustering with Normalized Cuts
NormalizedCutClustering
- 进行normalized cut算法的图像分割-Normalized cut algorithm for image segmentation
Ncut
- 自己写的Normalized Cut图像分割，聚类程序，程序非常清晰，花了很长时间调试。-Normalize Cut
ncut_multiscale
- 多尺度normalized cut分割的matlab代码 -Multiscale Normalized Cuts Segmentation Toolbox
Ncut
- 本文介绍了web文本聚类的流程，着重介绍了Normalized Cut谱聚类的原理和算法，提出以Minimum cut作为类内部的内聚强度作为衡量Normalized Cut的迭代停止条件
fenshuilingsuanfa
- 基于分水岭算法和图论的图像分割，所使用的方法为分水岭算法和Normalized Cut方法-Based on watershed algorithm and graph theory, image segmentation, the method used as a watershed algorithm and Normalized Cut method
NORMALIZED_CUT
- Normalized Cut for image segmentation
Clustering-src
- normalized cut clusterin algorithm.
graph-based-image-segmentation
- 五种当前主要的基于图的图像分割方法（normalized cut, min-cut/max-flow, isoperimetric partitioning, minimum spanning tree and random walker）的论文原文。-The original papers of five main graph-based image segmentation methods. They are normalized
Normalized-Cut
- Normalized Cut图像分割程序，matlab代码实现-Normalized Cut image segmentation procedure, Matlab code implementation
Normalized-cut-Image_7
- normalized cut for mulatipoint
Normalized-Cut
- normalized cut image