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30案例源码

于 2020-07-08 发布
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下载积分: 1 下载次数: 2

代码说明:

说明:  matlab中的三十个经典机器学习案例源码(30 classical machine learning cases while coding with Matlab.)

文件列表:

30案例源码, 0 , 2020-02-06
30案例源码\.DS_Store, 8196 , 2020-02-10
__MACOSX, 0 , 2020-02-10
__MACOSX\30案例源码, 0 , 2020-02-10
__MACOSX\30案例源码\._.DS_Store, 120 , 2020-02-10
30案例源码\chapter22.rar, 2690 , 2011-11-15
__MACOSX\30案例源码\._chapter22.rar, 230 , 2011-11-15
30案例源码\chapter1, 0 , 2020-02-06
30案例源码\chapter1\example2.m, 2113 , 2010-10-31
__MACOSX\30案例源码\chapter1, 0 , 2020-02-10
__MACOSX\30案例源码\chapter1\._example2.m, 230 , 2010-10-31
30案例源码\chapter1\example1.m, 1909 , 2010-10-31
__MACOSX\30案例源码\chapter1\._example1.m, 286 , 2010-10-31
__MACOSX\30案例源码\._chapter1, 194 , 2020-02-06
30案例源码\chapter1.rar, 2171 , 2011-11-15
__MACOSX\30案例源码\._chapter1.rar, 286 , 2011-11-15
30案例源码\chapter23.rar, 3155 , 2011-11-15
__MACOSX\30案例源码\._chapter23.rar, 230 , 2011-11-15
30案例源码\chapter21.rar, 713 , 2011-11-15
__MACOSX\30案例源码\._chapter21.rar, 230 , 2011-11-15
30案例源码\chapter3.rar, 4721 , 2011-11-15
__MACOSX\30案例源码\._chapter3.rar, 230 , 2011-11-15
30案例源码\chapter2.rar, 26677 , 2011-11-15
__MACOSX\30案例源码\._chapter2.rar, 230 , 2011-11-15
30案例源码\chapter20.rar, 11565 , 2011-11-15
__MACOSX\30案例源码\._chapter20.rar, 230 , 2011-11-15
30案例源码\chapter24.rar, 5685 , 2011-11-15
__MACOSX\30案例源码\._chapter24.rar, 230 , 2011-11-15
30案例源码\chapter30.rar, 176221 , 2011-11-15
__MACOSX\30案例源码\._chapter30.rar, 230 , 2011-11-15
30案例源码\chapter18.rar, 7649 , 2011-11-15
__MACOSX\30案例源码\._chapter18.rar, 230 , 2011-11-15
30案例源码\chapter6.rar, 628 , 2011-11-15
__MACOSX\30案例源码\._chapter6.rar, 230 , 2011-11-15
30案例源码\chapter7.rar, 4128 , 2011-11-15
__MACOSX\30案例源码\._chapter7.rar, 230 , 2011-11-15
30案例源码\chapter19.rar, 5002 , 2011-11-15
__MACOSX\30案例源码\._chapter19.rar, 230 , 2011-11-15
30案例源码\chapter25.rar, 173147 , 2011-11-15
__MACOSX\30案例源码\._chapter25.rar, 230 , 2011-11-15
30案例源码\chapter27.rar, 2503 , 2011-11-15
__MACOSX\30案例源码\._chapter27.rar, 230 , 2011-11-15
30案例源码\chapter5.rar, 94364 , 2011-11-15
__MACOSX\30案例源码\._chapter5.rar, 230 , 2011-11-15
30案例源码\chapter4.rar, 7260 , 2011-11-15
__MACOSX\30案例源码\._chapter4.rar, 230 , 2011-11-15
30案例源码\chapter26.rar, 2955 , 2011-11-15
__MACOSX\30案例源码\._chapter26.rar, 230 , 2011-11-15
30案例源码\chapter17.rar, 32669 , 2011-11-15
__MACOSX\30案例源码\._chapter17.rar, 230 , 2011-11-15
30案例源码\chapter9.rar, 705 , 2011-11-15
__MACOSX\30案例源码\._chapter9.rar, 230 , 2011-11-15
30案例源码\chapter8.rar, 3171 , 2011-11-15
__MACOSX\30案例源码\._chapter8.rar, 230 , 2011-11-15
30案例源码\chapter16.rar, 18584 , 2011-11-15
__MACOSX\30案例源码\._chapter16.rar, 230 , 2011-11-15
30案例源码\chapter28.rar, 8570 , 2011-11-15
__MACOSX\30案例源码\._chapter28.rar, 230 , 2011-11-15
30案例源码\chapter14.rar, 144753 , 2011-11-15
__MACOSX\30案例源码\._chapter14.rar, 230 , 2011-11-15
30案例源码\chapter15.rar, 12427 , 2011-11-15
__MACOSX\30案例源码\._chapter15.rar, 230 , 2011-11-15
30案例源码\chapter29.rar, 4393 , 2011-11-15
__MACOSX\30案例源码\._chapter29.rar, 230 , 2011-11-15
30案例源码\chapter11.rar, 10963 , 2011-11-15
__MACOSX\30案例源码\._chapter11.rar, 230 , 2011-11-15
30案例源码\chapter10.rar, 2577 , 2011-11-15
__MACOSX\30案例源码\._chapter10.rar, 230 , 2011-11-15
30案例源码\chapter12.rar, 28671 , 2011-11-15
__MACOSX\30案例源码\._chapter12.rar, 230 , 2011-11-15
30案例源码\chapter13.rar, 734874 , 2011-11-15
__MACOSX\30案例源码\._chapter13.rar, 230 , 2011-11-15
__MACOSX\._30案例源码, 194 , 2020-02-06

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0 个回复

  • bianyima
    该程序在matlab环境下完成抽样量化编码功能(非均匀量化)。(err)
    2008-06-18 00:30:33下载
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    The Cross Bilateral filter can enhance the PSNR of multi focus images that is in image fuison. Bilateral filtering is a local, nonlinear and non- iterative technique which combines a classical low-pass filter with an edge stopping function that attenuates the filter kernel when the intensity difference between pixels is large. As both gray level similarities and geometric closeness of the neighboring pixels are considered, the weights of the filter depend not only on Mahalanobis distance but also on the distance in gray/color space. The advantage of the filter is that it smoothes the image while preserving edges using neighboring pixels. CBF considers both gray-level similarities and geometric closeness of neighboring pixels in image one to shape the filter kernel and filters the image two.
    2015-03-10 16:53:31下载
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