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文件名称:k-meansPBOF

  • 所属分类：
    Special Effects
  • 标签属性：
    [Matlab] [源码]
  • 上传时间：
    2016-11-28
  • 文件大小：
    19.44mb
  • 已下载：
    0次
  • 提 供 者：
    王***
  • 相关连接：
    无
  • 下载说明：
    别用迅雷下载，失败请重下，重下不扣分！
修正介绍说明

介绍说明－－下载内容来自于网络，使用问题请自行百度

BOF算法（图像检索算法）和kmeans（迭代）进行聚类，实现图像检索-BOF algorithm (image retri　algorithm) and kmeans (use function extremum obtained by the method of adjustment rules iteration) cluster
(系统自动生成,下载前可以参看下载内容)

下载文件列表

文件名大小更新时间
k-means+BOF/do_demo.m
k-means+BOF/
k-means+BOF/K_Means.m
k-means+BOF/SIFT_feature/
k-means+BOF/SIFT_feature/.DS_Store
k-means+BOF/SIFT_feature/._.DS_Store
k-means+BOF/SIFT_feature/._do_database.m
k-means+BOF/SIFT_feature/._do_descriptor.m
k-means+BOF/SIFT_feature/._do_sift.m
k-means+BOF/SIFT_feature/demo-data/
k-means+BOF/SIFT_feature/demo-data/1.jpg
k-means+BOF/SIFT_feature/demo-data/2.jpg
k-means+BOF/SIFT_feature/demo-data/5.jpg
k-means+BOF/SIFT_feature/demo-data/6.jpg
k-means+BOF/SIFT_feature/demo-data/7.jpg
k-means+BOF/SIFT_feature/demo-data/GML_RANSAC_Matlab_Toolbox_0[1].2.rar
k-means+BOF/SIFT_feature/demo-data/beaver11.bmp
k-means+BOF/SIFT_feature/demo-data/beaver13.bmp
k-means+BOF/SIFT_feature/demo-data/einstein.pgm
k-means+BOF/SIFT_feature/demo-data/harrisandransac.rar
k-means+BOF/SIFT_feature/demo-data/image068.JPG
k-means+BOF/SIFT_feature/demo-data/image069.JPG
k-means+BOF/SIFT_feature/demo-data/image1.jpg
k-means+BOF/SIFT_feature/demo-data/image10.jpg
k-means+BOF/SIFT_feature/demo-data/image11.jpg
k-means+BOF/SIFT_feature/demo-data/image2.jpg
k-means+BOF/SIFT_feature/demo-data/image3.jpg
k-means+BOF/SIFT_feature/demo-data/image4.jpg
k-means+BOF/SIFT_feature/demo-data/image5.jpg
k-means+BOF/SIFT_feature/demo-data/image6.jpg
k-means+BOF/SIFT_feature/demo-data/image7.jpg
k-means+BOF/SIFT_feature/demo-data/image8.jpg
k-means+BOF/SIFT_feature/demo-data/replace1.jpg
k-means+BOF/SIFT_feature/demo-data/replace2.jpg
k-means+BOF/SIFT_feature/demo-data/view01.png
k-means+BOF/SIFT_feature/demo-data/view02.png
k-means+BOF/SIFT_feature/do_database.m
k-means+BOF/SIFT_feature/do_descriptor.m
k-means+BOF/SIFT_feature/do_diffofg.m
k-means+BOF/SIFT_feature/do_extrefine.m
k-means+BOF/SIFT_feature/do_gaussian.m
k-means+BOF/SIFT_feature/do_localmax.m
k-means+BOF/SIFT_feature/do_orientation.m
k-means+BOF/SIFT_feature/do_sift.m
k-means+BOF/SIFT_feature/smooth.m
k-means+BOF/SIFT_feature/util/
k-means+BOF/SIFT_feature/util/appendimages.m
k-means+BOF/SIFT_feature/util/plotsiftframe.m
k-means+BOF/SIFT_feature/util/plotss.m
k-means+BOF/SIFT_feature/util/tightsubplot.m
k-means+BOF/do_eucidean_distance.m
k-means+BOF/get_countVectors.m
k-means+BOF/get_sifts.m
k-means+BOF/get_singleVector.m
k-means+BOF/img_paths.txt
k-means+BOF/sourcePictures/
k-means+BOF/sourcePictures/023b5bb5c9ea15ce3288855bb2003af33a87b279.jpg
k-means+BOF/sourcePictures/503d269759ee3d6d9250db1747166d224e4ade5c.jpg
k-means+BOF/sourcePictures/7c1ed21b0ef41bd5e97f515754da81cb39db3d60.jpg
k-means+BOF/sourcePictures/8cb1cb1349540923db22c1a29658d109b2de49a6.jpg
k-means+BOF/sourcePictures/aa18972bd40735faa1bbec659a510fb30e2408a6.jpg
k-means+BOF/sourcePictures/b8389b504fc2d5626e417231e31190ef77c66ca5.jpg
k-means+BOF/sourcePictures/c2cec3fdfc039245e48843d38394a4c27d1e2528.jpg
k-means+BOF/sourcePictures/u=10034508483567703515&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10037027841303766552&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10091986201163828896&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10159683803006289805&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10230670253494031433&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=1026647772887727247&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10315791111158625148&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10327876331777850618&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10329749853294957225&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10332272662292110020&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10356866533043481785&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10362377972031184701&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10406211271299365260&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10468934591129331914&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10536686953381766889&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10547672733246804709&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10548598602252825443&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10614024623224228490&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10709880742322259893&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10861720154232069477&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10929802192364845692&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10930926502809890320&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=10940419831541205142&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=1110551312714916493&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11164994044093431553&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11215842751614108293&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11298708252689866506&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11390262833334582436&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11495558822369646950&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=1151319097730971848&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=1154264306261098183&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11553816921886416365&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11593573343011918649&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11641112402748670978&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=11675637051572073022&fm=21&gp=0.jpg
k-means+BOF/sourcePictures/u=117865892813794461

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