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改进svm

于 2021-03-06 发布
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下载积分: 1 下载次数: 10

代码说明:

说明:  phog方法提取图像特征,svm支持向量机进行分类,分别有GA遗传算法和PSO粒子群优化算法进行寻优。(Phog method extracted image features, SVM support vector machine classification, respectively, GA genetic algorithm and PSO particle swarm optimization algorithm for optimization.)

文件列表:

1_30.jpg, 7107 , 2020-04-21
1_30.jpg.txt, 4237 , 2020-05-24
2_30.jpg, 51795 , 2020-04-21
3_30.jpg, 37510 , 2020-04-21
4_30.jpg, 20977 , 2020-04-21
5_30.jpg, 66186 , 2020-04-21
Accuracy_GA_SVM.m, 1232 , 2020-05-09
Accuracy_PSO_SVM.m, 1233 , 2020-05-23
Accuracy_SVM.m, 1225 , 2020-05-23
anna_binMatrix.m, 1455 , 2020-05-04
anna_phog.m, 1818 , 2020-05-04
anna_phog_demo.m, 170 , 2020-05-24
anna_phogDescriptor.m, 1215 , 2020-05-04
Demo-image, 0 , 2020-05-09
Demo-image\0.jpg, 156403 , 2015-05-27
Demo-image\1.jpg, 91161 , 2015-05-27
Demo-image\10.jpg, 4101 , 2013-03-24
Demo-image\11.jpg, 156581 , 2015-05-27
Demo-image\12.jpg, 22357 , 2015-05-27
Demo-image\13.jpg, 11730 , 2013-03-24
Demo-image\14.jpg, 15632 , 2013-03-24
Demo-image\2.jpg, 155563 , 2015-05-27
Demo-image\3.jpg, 52060 , 2015-05-27
Demo-image\4.jpg, 127184 , 2015-05-27
Demo-image\5.jpg, 13811 , 2013-03-24
Demo-image\6.jpg, 16727 , 2013-03-24
Demo-image\7.jpg, 151037 , 2015-05-27
Demo-image\8.jpg, 138947 , 2015-05-27
Demo-image\9.jpg, 14759 , 2013-03-24
Demo-image\test, 0 , 2020-05-09
Demo-image\test\0.jpg, 52667 , 2020-04-21
Demo-image\test\0.jpg.txt, 5970 , 2020-04-23
Demo-image\test\1.jpg, 45562 , 2020-04-21
Demo-image\test\1.jpg.txt, 4633 , 2020-04-23
Demo-image\test\10.jpg, 56504 , 2020-04-21
Demo-image\test\10.jpg.txt, 4671 , 2020-04-23
Demo-image\test\11.jpg, 22861 , 2020-04-21
Demo-image\test\11.jpg.txt, 2884 , 2020-04-23
Demo-image\test\12.jpg, 13102 , 2020-04-21
Demo-image\test\12.jpg.txt, 5532 , 2020-04-23
Demo-image\test\13.jpg, 14343 , 2020-04-21
Demo-image\test\13.jpg.txt, 5435 , 2020-04-23
Demo-image\test\14.jpg, 19155 , 2020-04-23
Demo-image\test\14.jpg.txt, 6320 , 2020-04-23
Demo-image\test\2.jpg, 20783 , 2020-04-21
Demo-image\test\2.jpg.txt, 4115 , 2020-04-23
Demo-image\test\3.jpg, 53974 , 2020-04-21
Demo-image\test\3.jpg.txt, 5542 , 2020-04-23
Demo-image\test\4.jpg, 13718 , 2020-04-21
Demo-image\test\4.jpg.txt, 5774 , 2020-04-23
Demo-image\test\5.jpg, 9475 , 2020-04-21
Demo-image\test\5.jpg.txt, 4666 , 2020-04-23
Demo-image\test\6.jpg, 47424 , 2020-04-21
Demo-image\test\6.jpg.txt, 5205 , 2020-04-23
Demo-image\test\7.jpg, 34818 , 2020-04-21
Demo-image\test\7.jpg.txt, 5374 , 2020-04-23
Demo-image\test\8.jpg, 11194 , 2020-04-21
Demo-image\test\8.jpg.txt, 5287 , 2020-04-23
Demo-image\test\9.jpg, 3859 , 2020-04-21
Demo-image\test\9.jpg.txt, 2979 , 2020-04-23
Demo-image\u=2140437051,2007055591&fm=26&gp=0.jpg, 8892 , 2020-05-09
Demo.m, 1244 , 2020-04-23
GA_SVM_Demo.m, 973 , 2020-05-06
gaSVMcgForClass.m, 4351 , 2020-04-23
PSO_SVM_Demo.m, 807 , 2020-05-23
psoSVMcgForClass.m, 5928 , 2020-05-09
SVM_outputPicture.m, 2256 , 2020-05-24
test, 0 , 2020-05-09
test\1_01.jpg, 47431 , 2020-04-21
test\1_01.jpg.txt, 5465 , 2020-05-23
test\1_02.jpg, 11212 , 2020-04-21
test\1_02.jpg.txt, 4858 , 2020-05-23
test\1_03.jpg, 7350 , 2020-04-21
test\1_03.jpg.txt, 4096 , 2020-05-23
test\1_04.jpg, 12249 , 2020-04-21
test\1_04.jpg.txt, 5753 , 2020-05-23
test\1_05.jpg, 11837 , 2020-04-21
test\1_05.jpg.txt, 6228 , 2020-05-23
test\1_06.jpg, 10258 , 2020-04-21
test\1_06.jpg.txt, 5186 , 2020-05-23
test\1_07.jpg, 10492 , 2020-04-21
test\1_07.jpg.txt, 5177 , 2020-05-23
test\1_08.jpg, 10399 , 2020-04-21
test\1_08.jpg.txt, 4980 , 2020-05-23
test\1_09.jpg, 52667 , 2020-04-21
test\1_09.jpg.txt, 5970 , 2020-05-23
test\1_10.jpg, 50159 , 2020-04-21
test\1_10.jpg.txt, 5165 , 2020-05-23
test\2_01.jpg, 43136 , 2020-04-21
test\2_01.jpg.txt, 5450 , 2020-05-23
test\2_02.jpg, 41310 , 2020-04-21
test\2_02.jpg.txt, 5863 , 2020-05-23
test\2_03.jpg, 41105 , 2020-04-21
test\2_03.jpg.txt, 5690 , 2020-05-23
test\2_04.jpg, 64072 , 2020-04-21
test\2_04.jpg.txt, 6231 , 2020-05-23
test\2_05.jpg, 46495 , 2020-04-21
test\2_05.jpg.txt, 5142 , 2020-05-23
test\2_06.jpg, 9630 , 2020-04-21
test\2_06.jpg.txt, 4856 , 2020-05-23

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    2014-11-02 14:17:56下载
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    使用Splitting算法和GLA算法实现对图像的矢量量化及重新编码和重建。(Vector Quantization:To generate a 16-codeword codebook using Splitting Algorithm and GLA,then use this codebook to code the training image and reconstuct it.)
    2013-11-07 21:32:18下载
    积分:1
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    积分:1
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    2008-12-13 11:13:56下载
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    积分:1
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    说明:  吴恩达第五周作业。学习算法分两部分进行理解,第一部分是根据code对算法进行综述,第二部分是代码(The learning algorithm is divided into two parts, the first part is to summarize the algorithm according to the code, the second part is the code)
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    图像反卷积 来自D. Krishnan, R. Fergus中提到的方法(image deconvolution The Matlab functions in this directory solve the deconvolution problem in the paper D. Krishnan, R. Fergus: "Fast Image Deconvolution using Hyper-Laplacian Priors", Proceedings of NIPS 2009. )
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    实现了图片及目标图片的傅立叶变换,并得出了加载到空间光调制器上的相息图!(To achieve the target image and the image of the Fourier transform, and load to obtain a kinoform spatial light modulator on!)
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