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SWImage
- The Swendsen-Wang Cuts algorithm is used to label atomic regions (superpixels) based on their intensity patterns using generative models in a Bayesian framework. The prior is based on areas of connected components, which provides a clean segmentation
c_inference_ver2.2
- The package includes 3 Matlab-interfaces to the c-code: 1. inference.m An interface to the full inference package, includes several methods for approximate inference: Loopy Belief Propagation, Generalized Belief Propagation, Mean-Field
BayesianCoSegmentationOfMultipleMRImages
- 分割是在MRI analysis.We的基本问题之一,同时考虑了多种MR图像分割,其中,例如,可能是一个系列的问题经过一段时间的扫描相同的组织(的2D/3D)图像,图像的数量,或不同的切片图像的对称部分。 MR图像的多是分割份额常见的结构信息,因此他们可以协助彼此分割的程序。我们提出了一个贝叶斯共同分割算法在共享的信息整个图像是通过利用马尔可夫随机场前,和吉布斯采样后采样是有效的聘用。由于我们的共同拉动分割算法考虑到所有的图像信息的同时,它提供比个人更准确和坚实的结果分割,如支持从模拟和实际结果
nsct
- Contourlet 变换的平移不变性在奇异性方面导致了伪Gibbs 效应。而NSCT是一种平移不变、多尺度和多分辨率的冗余变换,它对滤波器上采样再进行分析和综合滤波,这种滤波器的设计及重构易于实现,能更好地采集频率且具规律性,在图像去噪中得到了广泛的应用。-Contourlet transform translation invariance in singularity aspects led to the pseudo Gibbs effect. And NSCT is a kind o
mmse_mrf_demo-1.1
- 图像去噪-A Generative Perspective on MRFs in Low-Level Vision-A Generative Perspective on MRFs in Low-Level Vision Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative
ibp
- Included in this distribution is matlab code to generate posterior samples for linear Gaussian and binary matrix factorization (noisy-or) Indian Buffet Process models. Three different posterior sampling algorithms are provided: Gibbs, reversibl
FAVAR
- 运用GIBBS抽样方式计算FAVAR模型(Using GIBBS sampling method to calculate FAVAR model)
BBE_Ddisk
- 用gibbs抽样和两步法方式拟合计算FAVAR模型(Fitting FAVAR model with Gibbs sampling method)