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文件名称:CNN-pooling-strategy

  • 所属分类：
    Graph Recognize
  • 标签属性：
    [Matlab] [源码]
  • 上传时间：
    2017-03-01
  • 文件大小：
    28.17mb
  • 已下载：
    0次
  • 提 供 者：
    李****
  • 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！
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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

基于卷积层和池化层的卷积深度网络被执行，该框架可以有效地识别灰度图像，彩色图像和高光谱图像。- Convolution deep network based on　convolution layer and pooling layer is performed, the framework can effectively identify grayscale images, color images and hyperspectral images.
(系统自动生成,下载前可以参看下载内容)

下载文件列表

CNN/cnnapplygrads.asv
CNN/cnnapplygrads.m
CNN/cnnbp - 副本.m
CNN/cnnbp.asv
CNN/cnnbp.m
CNN/cnnff.asv
CNN/cnnff.m
CNN/cnnnumgradcheck.m
CNN/cnnsetup.m
CNN/cnntest.m
CNN/cnntrain.m
CNN/MaxPooling.cpp
CNN/MaxPooling.cpp.bak
CNN/MaxPooling.m
CNN/MaxPooling.mexw32
CNN/MaxPooling.mexw64
CNN/MaxPoolingGPU.cpp
CNN/MaxPoolingGPU.cpp.bak
CNN/StochasticPooling.cpp
CNN/StochasticPooling.mexw64
CNN/StochaticTest.m
CNN/test_example_CNN.asv
CNN/test_example_CNN.m
data/mnist_uint8.mat
util/allcomb.m
util/expand.m
util/flicker.m
util/flipall.m
util/fliplrf.m
util/flipudf.m
util/im2patches.m
util/isOctave.m
util/makeLMfilters.m
util/myOctaveVersion.m
util/normalize.m
util/patches2im.m
util/randcorr.m
util/randp.m
util/rnd.m
util/sigm.m
util/sigmrnd.m
util/softmax.m
util/tanh_opt.m
util/visualize.m
util/whiten.m
util/zscore.m
CNN
data
util
67506287CNN-with-three-pooling-strategy/CNN/cnnapplygrads.asv
67506287CNN-with-three-pooling-strategy/CNN/cnnapplygrads.m
67506287CNN-with-three-pooling-strategy/CNN/cnnbp - 副本.m
67506287CNN-with-three-pooling-strategy/CNN/cnnbp.asv
67506287CNN-with-three-pooling-strategy/CNN/cnnbp.m
67506287CNN-with-three-pooling-strategy/CNN/cnnff.asv
67506287CNN-with-three-pooling-strategy/CNN/cnnff.m
67506287CNN-with-three-pooling-strategy/CNN/cnnnumgradcheck.m
67506287CNN-with-three-pooling-strategy/CNN/cnnsetup.m
67506287CNN-with-three-pooling-strategy/CNN/cnntest.m
67506287CNN-with-three-pooling-strategy/CNN/cnntrain.m
67506287CNN-with-three-pooling-strategy/CNN/MaxPooling.cpp
67506287CNN-with-three-pooling-strategy/CNN/MaxPooling.cpp.bak
67506287CNN-with-three-pooling-strategy/CNN/MaxPooling.m
67506287CNN-with-three-pooling-strategy/CNN/MaxPooling.mexw32
67506287CNN-with-three-pooling-strategy/CNN/MaxPooling.mexw64
67506287CNN-with-three-pooling-strategy/CNN/MaxPoolingGPU.cpp
67506287CNN-with-three-pooling-strategy/CNN/MaxPoolingGPU.cpp.bak
67506287CNN-with-three-pooling-strategy/CNN/StochasticPooling.cpp
67506287CNN-with-three-pooling-strategy/CNN/StochasticPooling.mexw64
67506287CNN-with-three-pooling-strategy/CNN/StochaticTest.m
67506287CNN-with-three-pooling-strategy/CNN/test_example_CNN.asv
67506287CNN-with-three-pooling-strategy/CNN/test_example_CNN.m
67506287CNN-with-three-pooling-strategy/data/mnist_uint8.mat
67506287CNN-with-three-pooling-strategy/util/allcomb.m
67506287CNN-with-three-pooling-strategy/util/expand.m
67506287CNN-with-three-pooling-strategy/util/flicker.m
67506287CNN-with-three-pooling-strategy/util/flipall.m
67506287CNN-with-three-pooling-strategy/util/fliplrf.m
67506287CNN-with-three-pooling-strategy/util/flipudf.m
67506287CNN-with-three-pooling-strategy/util/im2patches.m
67506287CNN-with-three-pooling-strategy/util/isOctave.m
67506287CNN-with-three-pooling-strategy/util/makeLMfilters.m
67506287CNN-with-three-pooling-strategy/util/myOctaveVersion.m
67506287CNN-with-three-pooling-strategy/util/normalize.m
67506287CNN-with-three-pooling-strategy/util/patches2im.m
67506287CNN-with-three-pooling-strategy/util/randcorr.m
67506287CNN-with-three-pooling-strategy/util/randp.m
67506287CNN-with-three-pooling-strategy/util/rnd.m
67506287CNN-with-three-pooling-strategy/util/sigm.m
67506287CNN-with-three-pooling-strategy/util/sigmrnd.m
67506287CNN-with-three-pooling-strategy/util/softmax.m
67506287CNN-with-three-pooling-strategy/util/tanh_opt.m
67506287CNN-with-three-pooling-strategy/util/visualize.m
67506287CNN-with-three-pooling-strategy/util/whiten.m
67506287CNN-with-three-pooling-strategy/util/zscore.m
67506287CNN-with-three-pooling-strategy/CNN
67506287CNN-with-three-pooling-strategy/data
67506287CNN-with-three-pooling-strategy/util
67506287CNN-with-three-pooling-strategy

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