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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Description: 包括kf，ekf，pf，upf可以自己定制模型参数，完成滤波-ReBEL currently contains most of the following functional units which can be used for state-, parameter- and joint-estimation:
Kalman filter
Extended Kalman filter
Sigma-Point Kalman filters (SPKF)
Unscented Kalman filter (UKF)
Central difference Kalman filter (CDKF)
Square-root SPKFs
Gaussian mixture SPKFs
Iterated SPKF
SPKF smoothers
Particle filters
Generic SIR particle filter
Gaussian sum particle filter
Sigma-point particle filter
Gaussian mixture sigma-point particle filter
Rao-Blackwellized particle filters
The italicized algorithms above are not fully functional yet (or included in the current release), but will be in the next or future releases. The code is designed to be as general, modular and extensible as possible, while at the same time trying to be as computationally efficient as possible. It has been tested with Matlab 7.2 (R2006a).
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Description: 这是一个关于GP-ADF和GP-RTSS的工具箱，主要基于“Robust Filtering and Smoothing with Gaussian Processes这篇文章-This software package provides a Matlab implementation of the GP-ADF and the GP-RTSS as described in
Marc Peter Deisenroth, Ryan Turner, Marco F. Huber, Uwe D. Hanebeck, Carl Edward Rasmussen:
Robust Filtering and Smoothing with Gaussian Processes
in IEEE Transactions on Automatic Control (2012)
The software package also contains implementations of the following filters/smoothers:
- GP-ADF/GP-RTSS
- Gibbs-filter/Gibbs-RTSS [Deisenroth and Ohlsson, ACC 2011]
- EKF/EKS
- UKF/URTSS
- CKF/CKS
We provide a demo script:
demo_gprtss.m
The code requires MatlabR2007a or newer.
(C) Copyright 2012 by Marc Deisenroth
Permission is granted for anyone to copy, use, or modify this
software and accompanying documents for any uncommercial
purposes, provided this copyright notice is retained, and note is
made of any changes that have been made. This software and
documents are distributed without any warranty.
I d appreciate any feedback on the code (useful, buggy, ine Platform: |
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Author:李 |
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