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SVM-Classification

于 2021-04-07 发布 文件大小:3886KB
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代码说明：

  Matlab写的SVM图像分类程序，是完整的可运行的图像分类程序，高手可以研究一下。(Matlab write SVM image classification procedure is complete working image classification procedures, experts can look at.)

文件列表：

SVM分类程序
...........\AFEm.m,3458,2013-06-06
...........\bay_errorbar.m,5785,2013-06-06
...........\bay_initlssvm.m,2003,2013-06-06
...........\bay_lssvm.m,10345,2013-06-06
...........\bay_lssvmARD.m,8187,2013-06-06
...........\bay_modoutClass.m,9358,2013-06-06
...........\bay_optimize.m,5977,2013-06-06
...........\bay_rr.m,4312,2013-06-06
...........\bootsp.m,1631,2013-06-06
...........\bootstrap.m,282,2013-06-06
...........\changelssvm.m,5576,2013-06-06
...........\cilssvm.m,4462,2013-06-06
...........\code.m,4245,2013-06-06
...........\codedist_bay.m,2118,2013-06-06
...........\codedist_hamming.m,756,2013-06-06
...........\codedist_loss.m,2018,2013-06-06
...........\codelssvm.m,4126,2013-06-06
...........\code_ECOC.m,5197,2013-06-06
...........\code_MOC.m,550,2013-06-06
...........\code_OneVsAll.m,364,2013-06-06
...........\code_OneVsOne.m,579,2013-06-06
...........\comp.m,359,2013-06-06
...........\crossvalidate.m,5350,2013-06-06
...........\crossvalidatelssvm.m,3773,2013-06-06
...........\csa.m,2901,2013-06-06
...........\data1.txt,5998384,2013-06-06
...........\democlass.m,3459,2013-06-06
...........\democonfint.m,2143,2013-06-06
...........\demofun.m,3972,2013-06-06
...........\demomodel.m,4772,2013-06-06
...........\demomulticlass.m,2299,2013-06-06
...........\demo_fixedclass.m,2251,2013-06-06
...........\demo_fixedsize.m,3233,2013-06-06
...........\demo_yinyang.m,3447,2013-06-06
...........\denoise_kpca.m,3598,2013-06-06
...........\eign.m,3787,2013-06-06
...........\gcrossvalidate.m,3302,2013-06-06
...........\gcrossvalidatelssvm.m,2022,2013-06-06
...........\gridsearch.m,6927,2013-06-06
...........\initlssvm.m,3327,2013-06-06
...........\kentropy.m,2206,2013-06-06
...........\kernel_matrix.m,2636,2013-06-06
...........\kernel_matrix2.m,477,2013-06-06
...........\kpca.m,6137,2013-06-06
...........\latentlssvm.m,2398,2013-06-06
...........\leaveoneout.m,3667,2013-06-06
...........\leaveoneoutlssvm.m,2334,2013-06-06
...........\linesearch.m,3758,2013-06-06
...........\linf.m,313,2013-06-06
...........\lin_kernel.m,531,2013-06-06
...........\lssvm.m,1762,2013-06-06
...........\lssvmMATLAB.m,2082,2013-06-06
...........\mean_acc.mat,183,2013-06-06
...........\mean_time.mat,187,2013-06-06
...........\MeasureError.asv,725,2013-06-06
...........\MeasureError.m,790,2013-06-06
...........\medae.m,311,2013-06-06
...........\misclass.m,693,2013-06-06
...........\MLP_kernel.m,608,2013-06-06
...........\mse.m,285,2013-06-06
...........\plotlssvm.m,9963,2013-06-06
...........\poly_kernel.m,623,2013-06-06
...........\postlssvm.m,4838,2013-06-06
...........\predict.m,3485,2013-06-06
...........\predlssvm.m,5031,2013-06-06
...........\preimage_rbf.m,4452,2013-06-06
...........\prelssvm.m,6288,2013-06-06
...........\progress.m,1247,2013-06-06
...........\range.m,173,2013-06-06
...........\RBF_kernel.m,1105,2013-06-06
...........\rcrossvalidate.m,5945,2013-06-06
...........\rcrossvalidatelssvm.m,4085,2013-06-06
...........\ridgeregress.m,1436,2013-06-06
...........\ripley.mat,4100,2013-06-06
...........\robustlssvm.m,3216,2013-06-06
...........\roc.m,7496,2013-06-06
...........\rsimplex.m,9888,2013-06-06
...........\sample.asv,100,2013-06-06
...........\sample.m,100,2013-06-06
...........\simann.m,5845,2013-06-06
...........\simlssvm.m,6421,2013-06-06
...........\simplex.m,9778,2013-06-06
...........\smootherlssvm.m,1033,2013-06-06
...........\tbform.m,1936,2013-06-06
...........\test.data,2029542,2013-06-06
...........\test1.asv,38,2013-06-06
...........\test1.m,33,2013-06-06
...........\test2.asv,520,2013-06-06
...........\test2.m,522,2013-06-06
...........\test3.asv,3888,2013-06-06
...........\test3.m,4117,2013-06-06
...........\train.data,14512253,2013-06-06
...........\trainlssvm.m,8732,2013-06-06
...........\tri.asv,5120,2013-06-06
...........\tri.m,5316,2013-06-06
...........\trimmedmse.m,1711,2013-06-06
...........\tunelssvm.asv,22592,2013-06-06
...........\tunelssvm.m,22592,2013-06-06
...........\usps_t1.m,968,2013-06-06

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    图像质量评价指标：MSE，衡量融合图像相对于标准参考图像灰度的偏离程度。其值越小，说明复原图像和标准参考图像的差异越小，恢复效果越好。(Image quality evaluation MSE)
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    积分：1
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    2009-11-19 10:33:16下载
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    这是我编写的数学形态学处理灰度图像和二值图像的源代码，没有使用matlab自带的函数。可以实现膨胀、腐蚀以及开闭运算。(This is written in mathematical morphology of grayscale images and the source code of the binary image, do not use Matlab comes with function. Can achieve expansion, corrosion, and the opening and closing operation.)
    2020-07-16 10:18:49下载
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