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CNN-Toolbox

于 2016-03-22 发布 文件大小:14415KB
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  基于matlab的深度学习工具箱，该工具箱内包含一个基于手写识别的cnn模型，注释清晰。(Based on the depth of learning matlab toolbox, the toolbox contains within a model based on handwriting recognition cnn, clear notes.)

文件列表：

CNN Toolbox
...........\cnnapplygrads.m,731,2015-11-14
...........\cnnbp.m,3847,2015-11-14
...........\cnnexamples.m,2165,2016-01-04
...........\cnnexamples.m~,2135,2015-12-08
...........\cnnff.m,3594,2015-11-14
...........\cnnsetup.m,5427,2015-12-08
...........\cnnsetup.m~,5260,2015-12-08
...........\cnntest.m,432,2015-11-14
...........\cnntrain.m,2009,2015-12-08
...........\cnntrain.m~,1846,2015-11-14
...........\data
...........\....\mnist_uint8.mat,14735220,2012-09-24
...........\test.m,164,2016-01-04
...........\util
...........\....\allcomb.m,2618,2012-09-24
...........\....\expand.m,1958,2012-09-24
...........\....\flicker.m,208,2012-09-24
...........\....\flipall.m,80,2012-09-24
...........\....\fliplrf.m,543,2012-09-24
...........\....\flipudf.m,576,2012-09-24
...........\....\im2patches.m,198,2012-09-24
...........\....\makeLMfilters.m,1895,2012-09-24
...........\....\patches2im.m,242,2012-09-24
...........\....\randcorr.m,283,2012-09-24
...........\....\randp.m,2083,2012-09-24
...........\....\rnd.m,49,2012-09-24
...........\....\sigm.m,48,2012-09-24
...........\....\sigmrnd.m,126,2012-09-24
...........\....\softmax.m,256,2012-09-24
...........\....\visualize.m,1126,2012-09-24
...........\....\whiten.m,164,2012-09-24
...........\....\xunit
...........\....\.....\%2Bxunit
...........\....\.....\......\%2Butils
...........\....\.....\......\......\arrayToString.m,2972,2012-09-24
...........\....\.....\......\......\compareFloats.m,4376,2012-09-24
...........\....\.....\......\......\comparisonMessage.m,1005,2012-09-24
...........\....\.....\......\......\containsRegexp.m,600,2012-09-24
...........\....\.....\......\......\Contents.m,1048,2012-09-24
...........\....\.....\......\......\generateDoc.m,337,2012-09-24
...........\....\.....\......\......\isAlmostEqual.m,1233,2012-09-24
...........\....\.....\......\......\isSetUpString.m,519,2012-09-24
...........\....\.....\......\......\isTearDownString.m,540,2012-09-24
...........\....\.....\......\......\isTestCaseSubclass.m,894,2012-09-24
...........\....\.....\......\......\isTestString.m,589,2012-09-24
...........\....\.....\......\......\parseFloatAssertInputs.m,1627,2012-09-24
...........\....\.....\......\......\stringToCellArray.m,408,2012-09-24
...........\....\.....\assertElementsAlmostEqual.m,2559,2012-09-24
...........\....\.....\assertEqual.m,1383,2012-09-24
...........\....\.....\assertExceptionThrown.m,1925,2012-09-24
...........\....\.....\assertFalse.m,810,2012-09-24
...........\....\.....\assertFilesEqual.m,2548,2012-09-24
...........\....\.....\assertTrue.m,933,2012-09-24
...........\....\.....\assertVectorsAlmostEqual.m,2463,2012-09-24
...........\....\.....\CommandWindowTestRunDisplay.m,1215,2012-09-24
...........\....\.....\Contents.m,1820,2012-09-24
...........\....\.....\FunctionHandleTestCase.m,6649,2012-09-24
...........\....\.....\info.xml,712,2012-09-24
...........\....\.....\initTestSuite.m,1643,2012-09-24
...........\....\.....\runtests.m,4841,2012-09-24
...........\....\.....\TestCase.m,3525,2012-09-24
...........\....\.....\TestCaseInDir.m,1108,2012-09-24
...........\....\.....\TestCaseWithAddPath.m,1911,2012-09-24
...........\....\.....\TestComponent.m,1810,2012-09-24
...........\....\.....\TestComponentInDir.m,2160,2012-09-24
...........\....\.....\TestRunDisplay.m,9772,2012-09-24
...........\....\.....\TestRunLogger.m,3872,2012-09-24
...........\....\.....\TestRunMonitor.m,1334,2012-09-24
...........\....\.....\TestSuite.m,13145,2012-09-24
...........\....\.....\TestSuiteInDir.m,1850,2012-09-24
...........\....\.....\VerboseTestRunDisplay.m,3610,2012-09-24

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  • dianlixitongchaoliujishuan
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    积分：1
  • Untitled
    a.阅读的图像img_1.tif，img_2.png的文件夹中，并 他们展示于一体，这两个数字分别。 （参考函数：imread, imshow, figure, subplot） b.在matlab，观察从工作区中的图像信息面板 c.分别使用size, imfinfo,whos等功能获得的图像信息 d.添加标题的图像。 （参考函数：title） Ë 。下面的代码实现的M文件编辑器 f=imread(‘img_1.tif’) imshow(f) set(figure(1), NumberTitle , off , Name , my first image’) 观察结果，并确定的功set() f。保存img_1.tif目录“D： imagetest”。如果该文件夹不 存在，请首先创建这个新的文件夹。 （参考函数：imwrite） (a. Read the images img_1.tif, img_2.png given in the folder, and show them in one and two figures respectively. (referenced function: imread, imshow, figure, subplot) b. In matlab, observe the images information from the workspace Panel c. Use size, imfinfo,whos,etc functions to obtain image information respectively. d. Add title to the images. (referenced function: title) e. Implement the following codes in the M-file Editor f=imread(‘img_1.tif’) imshow(f) set(figure(1), NumberTitle , off , Name , my first image’) observe the result, and determine the function of set() f. Save img_1.tif to the directory “d:imagetest”. If the folder does not exist, please create this new folder first. (referenced function: imwrite))
    2013-04-26 09:26:40下载
    积分：1
  • Soft
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    2014-10-06 17:59:04下载
    积分：1
  • nm1
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    2011-11-21 18:54:07下载
    积分：1
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    2009-08-11 11:21:32下载
    积分：1
  • sourctoid
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    2009-02-28 14:22:33下载
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    image prcessing: histogram, negative, thresholding
    2009-11-15 08:31:17下载
    积分：1
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    This program describes that how the binary data is transmitted by dividing data into frames. it also analyse the Bit Error rate by 16 QAM method and viterbi decoding method.
    2014-12-04 00:33:14下载
    积分：1
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