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SVM_image_block_segment

于 2014-12-27 发布 文件大小:3434KB
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下载积分: 1 下载次数: 160

代码说明:

  SVM 用于基于块划分特征提取的图像分类,主要针对一幅图片的类型进行判断,比如说是古建筑、水体、植被等。(SVM classfication for image class type, based on image block segmention.)

文件列表:

SVM 用于基于块划分特征提取的图像分类

....................................\Data
....................................\....\100.png
....................................\....\101.png
....................................\....\102.png
....................................\....\103.png
....................................\....\104.png
....................................\....\105.png,122,2014-12-25
....................................\....\106.png,115,2014-12-25
....................................\....\107.png,125,2014-12-25
....................................\....\108.png,149,2014-12-25
....................................\....\109.png,164,2014-12-25
....................................\....\200.png,143,2014-12-25
....................................\....\201.png,167,2014-12-25
....................................\....\202.png,160,2014-12-25
....................................\....\203.png,158,2014-12-25
....................................\....\204.png,160,2014-12-25
....................................\....\205.png,155,2014-12-25
....................................\....\206.png,161,2014-12-25
....................................\....\207.png,154,2014-12-25
....................................\....\208.png,165,2014-12-25
....................................\....\209.png,159,2014-12-25
....................................\....\300.png,161,2014-12-25
....................................\....\301.png,167,2014-12-25
....................................\....\302.png,167,2014-12-25
....................................\....\303.png,163,2014-12-25
....................................\....\304.png,167,2014-12-25
....................................\....\305.png,167,2014-12-25
....................................\....\306.png,167,2014-12-25
....................................\....\307.png,167,2014-12-25
....................................\....\308.png,167,2014-12-25
....................................\....\309.png,158,2014-12-25
....................................\....\400.png,160,2014-12-25
....................................\....\401.png,160,2014-12-25
....................................\....\402.png,167,2014-12-25
....................................\....\403.png,167,2014-12-25
....................................\....\404.png,167,2014-12-25
....................................\....\405.png,156,2014-12-25
....................................\....\406.png,167,2014-12-25
....................................\....\407.png,167,2014-12-25
....................................\....\408.png,167,2014-12-25
....................................\....\409.png,165,2014-12-25
....................................\getFeature.m,1239,2014-12-25
....................................\getSubImageClass.m,1018,2014-12-25
....................................\photoclassify.m,1761,2014-12-25
....................................\rgb2hsv.m,1215,2011-02-28
....................................\sofm.m,1614,2014-12-25
....................................\svm图像分类.pdf,287064,2014-12-25

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