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Description: EM算法源程序的代码，运行的结果和实验报告。-EM algorithm source code, operating results and the experimental report.
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Size: 49152 |
Author: 郝保明 |
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Description: 德州扑克纸牌汉化版源码喜欢的自己下是php的源码-Chinese Version of Texas Hold' em poker, under its own source like
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Size: 2232320 |
Author: 李路美 |
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Description: 该演示中包含的代码演示如何氡相似的功能，可以用来提高（以及部分）在Connectome电磁图像单元格边界。
请举出下列文件如果您发现此代码有用：
Ritwik库马尔，阿梅里奥五雷纳和Hanspeter Pfister说“氡样的特点及其应用Connectomics”，接受，IEEE计算机学会研讨会在生物医学图像分析（MMBIA）2010年数学方法
http://seas.harvard.edu/〜 rkkumar
radonLikeFeaturesDemo.m：演示边缘增强用氡相似的功能，
getEdgeFeatures.m：助手为高斯函数的二阶导数滤波器
makeBarFilters.m：助手为高斯函数的二阶导数滤波器
sample.png：示例图像在此演示使用-The demo included in the code demonstrates how Radon-Like Features can be used to enhance (and segment) cell boundaries in Connectome EM images.
Please cite the following paper if you find this code useful:
Ritwik Kumar, Amelio V. Reina & Hanspeter Pfister, “Radon-Like Features and their Application to Connectomics”, accepted, IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) 2010
http://seas.harvard.edu/~rkkumar
radonLikeFeaturesDemo.m : Demonstrates edge enhancement using Radon-Like Features
getEdgeFeatures.m : Helper function for Gaussian Second Derivative Filters
makeBarFilters.m : Helper function for Gaussian Second Derivative Filters
sample.png : Sample image for use in this demo
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Size: 12288 |
Author: zhou |
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Description: 改进的meanShift算法，能够处理对象的旋转角度发生变化时的跟踪问题-An adaptive tracking algorithm,it s an improved MeanShift algorithm,can hanlde roation of the object during the tracking process
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Size: 7183360 |
Author: joe |
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Description: 用于求解带盒状约束的连续优化问题的类电磁机制算法(Electromagentism-like Mechanism Algorithm, EM)，该算法最早由Erasmus University的Birbil S. Ilker等人提出，是一种非常新颖且有效的智能算法。-The code realizes Electromagentism-like Mechanism Algorithm which is for solving continuous optimization problem with box-constraint. The algorithm was proposed by Birbil S. Ilker from Erasmus University.
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Size: 16384 |
Author: yxl |
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Description: This the MATLAB code that was used to produce the figures and tables in Section V of
F. Forbes and G. Fort, Combining Monte Carlo and mean-field like methods for inference
in Hidden Markov Random Fields, Accepted for publication in IEEE Trans. on Image
Processing, 2006.
1
MATLAB has the capability of running functions written in C. The files which hold the source
for these functions are called MEX-Files. Some functions of our codes are written in C.
The purpose of this software is to implement the MCVEM algorithm, described in the paper
mentioned above, when applied to Image Segmentation. MCVEM consists in combining approximation
techniques - based on variational EM - and simulation techniques - based on MCMC
-.
This software is the first version that is made publicly available.
2 How to
2.1 Obtain the source code
Download it from
http://www.tsi.enst.fr/gfort/INRIA/MCVEM.html
After unpacking the archive, you should obtain
• two-This is the MATLAB code that was used to produce the figures and tables in Section V of
F. Forbes and G. Fort, Combining Monte Carlo and mean-field like methods for inference
in Hidden Markov Random Fields, Accepted for publication in IEEE Trans. on Image
Processing, 2006.
1
MATLAB has the capability of running functions written in C. The files which hold the source
for these functions are called MEX-Files. Some functions of our codes are written in C.
The purpose of this software is to implement the MCVEM algorithm, described in the paper
mentioned above, when applied to Image Segmentation. MCVEM consists in combining approximation
techniques - based on variational EM - and simulation techniques - based on MCMC
-.
This software is the first version that is made publicly available.
2 How to
2.1 Obtain the source code
Download it from
http://www.tsi.enst.fr/gfort/INRIA/MCVEM.html
After unpacking the archive, you should obtain
• two
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Size: 692224 |
Author: jeevithajaikumar |
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Description: 以无约束优化问题为研究对象，基本的类电磁算法-Electromagnetism-like Mechanism，EM）
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Size: 1024 |
Author: 尜尜 |
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Description: Just like EM of Gaussian Mixture Model, this is the EM algorithm for fitting Bernoulli Mixture Model.
GMM is useful for clustering real value data. However, for binary data (such as bag of word feature) Bernoulli Mixture is more suitable.
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Size: 3072 |
Author: lin |
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Description: 本文以无约束优化问题为研究对象，研究了一种较新的元启发式算法，即类电磁机制算法（Electromagnetism-like Mechanism，EM），利用改进算法求解实际工程中的优化问题。-In this paper, a new heuristic algorithm, Electromagnetism-like Mechanism (EM), is studied by using the improved algorithm to solve the optimization problem in practical engineering.
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Size: 555008 |
Author: 高明慧 |
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