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CNN-for-Image-Retrieval-master

于 2019-05-05 发布 文件大小:2974KB
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代码说明：

  基于内容的CNN图像检索，编写语言为matlab(CNN Image Retrieval, matlab)

文件列表：

CNN-for-Image-Retrieval-master, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\.gitignore, 6 , 2017-10-07
CNN-for-Image-Retrieval-master\README.md, 5048 , 2017-10-07
CNN-for-Image-Retrieval-master\compute_MAP.m, 1982 , 2017-10-07
CNN-for-Image-Retrieval-master\database, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\database\001_accordion_image_0001.jpg, 25120 , 2017-10-07
CNN-for-Image-Retrieval-master\database\001_accordion_image_0002.jpg, 18640 , 2017-10-07
CNN-for-Image-Retrieval-master\database\001_accordion_image_0003.jpg, 25284 , 2017-10-07
CNN-for-Image-Retrieval-master\database\002_anchor_image_0001.jpg, 4945 , 2017-10-07
CNN-for-Image-Retrieval-master\database\002_anchor_image_0002.jpg, 12210 , 2017-10-07
CNN-for-Image-Retrieval-master\database\002_anchor_image_0003.jpg, 23032 , 2017-10-07
CNN-for-Image-Retrieval-master\database\003_ant_image_0001.jpg, 10067 , 2017-10-07
CNN-for-Image-Retrieval-master\database\003_ant_image_0002.jpg, 10756 , 2017-10-07
CNN-for-Image-Retrieval-master\database\003_ant_image_0003.jpg, 22111 , 2017-10-07
CNN-for-Image-Retrieval-master\database\1982.jpg, 8173 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClasses.txt, 39 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\accordion, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\accordion\image_0001.jpg, 25120 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\accordion\image_0002.jpg, 18640 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\accordion\image_0003.jpg, 25284 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\anchor, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\anchor\image_0001.jpg, 4945 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\anchor\image_0002.jpg, 12210 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\anchor\image_0003.jpg, 23032 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\ant, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\ant\image_0001.jpg, 10067 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\ant\image_0002.jpg, 10756 , 2017-10-07
CNN-for-Image-Retrieval-master\databaseClassified\ant\image_0003.jpg, 22111 , 2017-10-07
CNN-for-Image-Retrieval-master\extractCNN.m, 1964 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\.gitattributes, 119 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\.gitignore, 877 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\.gitmodules, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\COPYING, 735 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\Makefile, 9326 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\Makefile.mex, 801 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\Makefile.nvcc, 933 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\README.md, 363 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\Makefile, 3862 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\blocks.tex, 20196 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\figures, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\figures\imnet.pdf, 18884 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\figures\pepper.pdf, 702358 , 2017-10-07
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CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\fundamentals.tex, 21304 , 2017-10-07
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CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\impl.tex, 16705 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\intro.tex, 18899 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\matconvnet-manual.tex, 3773 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\matdoc.py, 7046 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\matdocparser.py, 11108 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\references.bib, 2729 , 2017-10-07
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CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\site\docs, 0 , 2017-10-07
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CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\site\docs\pretrained.md, 14586 , 2017-10-07
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CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\doc\site\docs\training.md, 1166 , 2017-10-07
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CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\examples\cifar\cnn_cifar.m, 5246 , 2017-10-07
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CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\examples\cnn_train.m, 14592 , 2017-10-07
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CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\examples\imagenet, 0 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\examples\imagenet\cnn_imagenet.m, 6984 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\examples\imagenet\cnn_imagenet_camdemo.m, 1677 , 2017-10-07
CNN-for-Image-Retrieval-master\matconvnet-1.0-beta17\examples\imagenet\cnn_imagenet_deploy.m, 5871 , 2017-10-07

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    说明：  用VC实现数字减影算法，通过模板匹配，再对两幅图像相减，即用盈片中减去蒙片，从而实现突出血管区域的目的。【源码加文档说明】(Using VC to achieve digital subtraction algorithm, template matching, and then the subtraction of two images, that the film with surplus minus mask, in order to achieve the purpose of highlighting vascular region. 【Source】 plus documented)
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