网站已改版,请使用新地址访问:点击访问
sparsecoding 稀疏编码在图像分类中的实现,自己写的matlab程序,带demo 259万源代码下载- www.pudn.com
 文件名称: sparsecoding下载  收藏√  [投票:非常好  5  4  3  2  1 投票:太差了]
  所属分类: matlab
  开发工具: matlab
  文件大小: 9001 KB
  上传时间: 2015-04-19
  下载次数: 188
  提 供 者: 曹恩泽
 详细说明:稀疏编码在图像分类中的实现,自己写的matlab程序,带demo-sparsecoding in image classification
文件列表(点击判断是否您需要的文件,如果是垃圾请在下面评价投诉):
  测试demo\Classification\codeSCW.m
  ........\..............\display_network.m
  ........\..............\generateImages.m
  ........\..............\getSparseCodingFeature.m
  ........\..............\Kits\kit\biggest.asv
  ........\..............\....\...\biggest.m
  ........\..............\....\...\distance.asv
  ........\..............\....\...\distance.m
  ........\..............\....\...\gradi.m
  ........\..............\....\...\kit01.asv
  ........\..............\....\...\localization.m
  ........\..............\....\...\mirror.m
  ........\..............\....\...\preproc.m
  ........\..............\....\...\stretch.m
  ........\..............\....\...\test.asv
  ........\..............\....\libsvm\libsvmpredict.mexw64
  ........\..............\....\......\libsvmtrain.mexw64
  ........\..............\....\minFunc\ArmijoBacktrack.m
  ........\..............\....\.......\autoGrad.m
  ........\..............\....\.......\autoHess.m
  ........\..............\....\.......\autoHv.m
  ........\..............\....\.......\autoTensor.m
  ........\..............\....\.......\callOutput.m
  ........\..............\....\.......\conjGrad.m
  ........\..............\....\.......\dampedUpdate.m
  ........\..............\....\.......\example_minFunc.m
  ........\..............\....\.......\example_minFunc_LR.m
  ........\..............\....\.......\isLegal.m
  ........\..............\....\.......\lbfgs.m
  ........\..............\....\.......\lbfgsC.c
  ........\..............\....\.......\lbfgsC.mexa64
  ........\..............\....\.......\lbfgsC.mexglx
  ........\..............\....\.......\lbfgsC.mexmac
  ........\..............\....\.......\lbfgsC.mexmaci
  ........\..............\....\.......\lbfgsC.mexmaci64
  ........\..............\....\.......\lbfgsC.mexw32
  ........\..............\....\.......\lbfgsC.mexw64
  ........\..............\....\.......\lbfgsUpdate.m
  ........\..............\....\.......\.ogistic\LogisticDiagPrecond.m
  ........\..............\....\.......\........\LogisticHv.m
  ........\..............\....\.......\........\LogisticLoss.m
  ........\..............\....\.......\........\mexutil.c
  ........\..............\....\.......\........\mexutil.h
  ........\..............\....\.......\........\mylogsumexp.m
  ........\..............\....\.......\........\repmatC.c
  ........\..............\....\.......\........\repmatC.dll
  ........\..............\....\.......\........\repmatC.mexglx
  ........\..............\....\.......\........\repmatC.mexmac
  ........\..............\....\.......\mchol.m
  ........\..............\....\.......\mcholC.c
  ........\..............\....\.......\mcholC.mexmaci64
  ........\..............\....\.......\mcholC.mexw32
  ........\..............\....\.......\mcholC.mexw64
  ........\..............\....\.......\mcholinc.m
  ........\..............\....\.......\minFunc.m
  ........\..............\....\.......\minFunc_processInputOptions.m
  ........\..............\....\.......\polyinterp.m
  ........\..............\....\.......\precondDiag.m
  ........\..............\....\.......\precondTriu.m
  ........\..............\....\.......\precondTriuDiag.m
  ........\..............\....\.......\rosenbrock.m
  ........\..............\....\.......\taylorModel.m
  ........\..............\....\.......\WolfeLineSearch.m
  ........\..............\loadPictureControllor.m
  ........\..............\localization.m
  ........\..............\model.mat
  ........\..............\myClassification.fig
  ........\..............\myClassification.m
  ........\..............\myModel.mat
  ........\..............\runClassification.m
  ........\..............\sample.m
  ........\..............\sparseCodingFeatureCost.m
  ........\..............\sparseCodingWeightCost.m
  ........\..............\trainSparseCoder.m
  ........\run.m
  ........\test\daqiao1-4-20131026071436-20131026075722-65388427-2245.png
  ........\....\daqiao1-4-20131026071436-20131026075722-65388427-4061.png
  ........\....\daqiao1-4-20131026071436-20131026075722-65388427-620.png
  ........\....\daqiao1-4-20131026071436-20131026075722-65388427-647.png
  ........\....\daqiao1-5-20131026093928-20131026102213-65388271-5108.png
  ........\....\daqiao1-5-20131026093928-20131026102213-65388271-6059.png
  ........\....\shengpingdasha-2-20131024041159-20131024082354-58950110-49404.png
  ........\....\shengpingdasha-2-20131024041159-20131024082354-58950110-65957.png
  ........\....\shengpingdasha-2-20131024041159-20131024082354-58950110-67527.png
  ........\....\shengpingdasha-3-20131024082358-20131024123551-58975429-207621.png
  ........\....\shengpingdasha-3-20131024082358-20131024123551-58975429-26023.png
  ........\....\shengpingdasha-3-20131024082358-20131024123551-58975429-61467.png
  ........\....\shengpingdasha-3-20131024082358-20131024123551-58975429-81009.png
  ........\....\shengpingdasha-4-20131024123557-20131024164756-58958908-35064.png
  ........\....\Untitled4.m
  ........\_运行run函数即可.txt
  ........\Classification\Kits\minFunc\logistic
  ........\..............\....\kit
  ........\..............\....\libsvm
  ........\..............\....\minFunc
  ........\..............\Kits
  ........\Classification
  ........\test
  测试demo
评价推荐↑  一般 有密码 和说明不符 不是源码或资料 文件不全  不能解压 纯粹是垃圾  留言
 [王瑶]:文件不全 [xiaozhang]:很好,推荐下载 [lichen]:一般,勉强可用 [新田]:很好,推荐下载
 输入关键字,在本站259万海量源码库中尽情搜索:  帮助
 [Roberts.rar] - Roberts edge detection algorithm
 [fuzzypredictive.rar] - 改进型的模糊预测控制算法matlab仿真程序,大家可以交流看一下
 [Slider-Step.zip] - This code calculates dimensionless pressure, and load carrying capacity for a finite width slider step bearing
 
 [stanford-deep-learning-matlab-code.rar] - stanford大学deep learning在线课程课后练习代码,我自己写的,可以参考一下。
 [code.rar] - 稀疏编码的工具包,用matlab实现,数学上是求解l1 norm最小化
 [SceneTextCNN_demo.tar.gz] - 端至端卷积神经网络的文字识别,代码演示包. 它包含我们的论文中使用的所有主要组成部分: kmeans无监督特征学习 + 卷积神经网络(CNN)
 [sparse-variable-BSS.rar] - 基于稀疏变量的欠定盲源分离,可以解决源数大于传感器数的问题,即欠定盲源分离问题。
 [eemd.zip] - 验模态分解(Empirical Mode Decomposition,简称EMD)是一种自适应信号分解方法,主要应用于非线性非平稳的信号。整体平均经验模态分解(Ensemble Empirical Mode Decomposition,简称EEMD)解决了EMD中出现的模态混合问题。
 [Image-Classification.rar] - 本文实现了09年CVPR的文章Linear Spatial Pyramid Matching using Sparse Coding for Image Classification
 [aaa.rar] - 关于遥感图像分类方面的程序源代码 有主成分分析,神经网络等方法