文件名称:[codes]LeNet-5
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2014-12-04
- 文件大小：
- 11.66mb
- 下载次数：
- 0次
- 提 供 者：
- 柳**
- 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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是matlab的代码，关于yann Lecun在89年提出的cnn的原型，这个代码成功应用于欧洲很多国家的手写支票识别-Is matlab code on cnn yann Lecun prototype made in 1989, this code successfully applied to handwriting recognition check many European countries
(系统自动生成,下载前可以参看下载内容)
下载文件列表
CNN_matlab代码
..............\license.txt
..............\ver 0.83
..............\........\@cnn
..............\........\....\adapt_dw.m
..............\........\....\calchx.m
..............\........\....\calcje.m
..............\........\....\calcMCR.m
..............\........\....\check_finit_dif.m
..............\........\....\cnn.m
..............\........\....\cnn_size.m
..............\........\....\cutrain.m
..............\........\....\init.m
..............\........\....\sim.m
..............\........\....\subsasgn.m
..............\........\....\subsref.m
..............\........\....\train.m
..............\........\back_conv2.m
..............\........\back_subsample.m
..............\........\changelog.txt
..............\........\changelog.txt~
..............\........\cnet.mat
..............\........\cnet_tool.m
..............\........\cnn2singlestruct.m
..............\........\cnn_gui.fig
..............\........\cnn_gui.m
..............\........\cucalcMCR.m
..............\........\cutrain_cnn.m
..............\........\fastFilter2.m
..............\........\license.txt
..............\........\license.txt~
..............\........\MNIST
..............\........\.....\t10k-images.idx3-ubyte
..............\........\.....\t10k-labels.idx1-ubyte
..............\........\.....\train-images.idx3-ubyte
..............\........\.....\train-labels.idx1-ubyte
..............\........\mse.m
..............\........\preproc_data.m
..............\........\preproc_image.m
..............\........\purelin.m
..............\........\rand_std.m
..............\........\readme.txt
..............\........\readMNIST.m
..............\........\readMNIST_image.m
..............\........\rot180.m
..............\........\singlestruct2cnn.m
..............\........\subsample.m
..............\........\tansig_mod.m
..............\........\test_dgt.m
..............\........\train_cnn.m