登录
首页 » matlab » Deep learning_CNN DBN RBM

Deep learning_CNN DBN RBM

于 2018-12-18 发布 文件大小:14409KB
0 197
下载积分: 1 下载次数: 48

代码说明:

  运用深度学习模型实现图像的分类,主要包括卷积神经网络CNN和深信度网络DBN(Classification of images using deep learning model includes convolutional neural network CNN and belief network DBN.)

文件列表:

深度学习CNN%2BDBN%2BRBM\.travis.yml, 249 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caeapplygrads.m, 1219 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caebbp.m, 917 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caebp.m, 1011 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caedown.m, 259 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caeexamples.m, 754 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caenumgradcheck.m, 3618 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caesdlm.m, 845 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caetrain.m, 1148 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\caeup.m, 489 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\max3d.m, 173 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\scaesetup.m, 1937 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE\scaetrain.m, 270 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CNN\cnnapplygrads.m, 575 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CNN\cnnbp.m, 2141 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CNN\cnnff.m, 1774 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CNN\cnnnumgradcheck.m, 3430 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CNN\cnnsetup.m, 2020 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CNN\cnntest.m, 193 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CNN\cnntrain.m, 845 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CONTRIBUTING.md, 544 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\create_readme.sh, 744 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\data\mnist_uint8.mat, 14735220 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\DBN\dbnsetup.m, 557 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\DBN\dbntrain.m, 232 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\DBN\dbnunfoldtonn.m, 425 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\DBN\rbmdown.m, 90 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\DBN\rbmtrain.m, 1401 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\DBN\rbmup.m, 89 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\LICENSE, 1313 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nnapplygrads.m, 628 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nnbp.m, 1638 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nnchecknumgrad.m, 704 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nneval.m, 811 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nnff.m, 1849 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nnpredict.m, 192 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nnsetup.m, 1844 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nntest.m, 184 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nntrain.m, 2414 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN\nnupdatefigures.m, 1858 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\README.md, 8861 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\README_header.md, 2244 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\REFS.md, 950 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\SAE\saesetup.m, 132 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\SAE\saetrain.m, 308 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\tests\runalltests.m, 165 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\tests\test_cnn_gradients_are_numerically_correct.m, 552 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\tests\test_example_CNN.m, 981 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\tests\test_example_DBN.m, 1031 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\tests\test_example_NN.m, 3247 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\tests\test_example_SAE.m, 934 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\tests\test_nn_gradients_are_numerically_correct.m, 749 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\allcomb.m, 2618 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\expand.m, 1958 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\flicker.m, 208 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\flipall.m, 80 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\fliplrf.m, 543 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\flipudf.m, 576 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\im2patches.m, 313 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\isOctave.m, 108 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\makeLMfilters.m, 1895 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\myOctaveVersion.m, 169 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\normalize.m, 97 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\patches2im.m, 242 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\randcorr.m, 283 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\randp.m, 2083 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\rnd.m, 49 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\sigm.m, 48 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\sigmrnd.m, 126 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\softmax.m, 256 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\tanh_opt.m, 54 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\visualize.m, 1072 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\whiten.m, 183 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util\zscore.m, 137 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CAE, 0 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\CNN, 0 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\data, 0 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\DBN, 0 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\NN, 0 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\SAE, 0 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\tests, 0 , 2015-12-01
深度学习CNN%2BDBN%2BRBM\util, 0 , 2015-12-01
深度学习CNN%2BDBN%2BRBM, 0 , 2015-12-01

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • 用python爬虫抓站的一些技巧总结
    用python爬虫抓站的实用技巧,学习python爬虫抓站的实用知识(Practical Skills of Python Crawler Grab Station)
    2019-03-18 09:26:51下载
    积分:1
  • 气温不起额武器恶趣味气 味人屋企 人我确认
    气温不起额武器恶趣味气 味人屋企 人我确认-qweqwe
    2022-03-03 20:47:42下载
    积分:1
  • 具有逻辑和算术运算符的十六进制评价和计算器
    Hex evaluation and calculator with logical and arithmetic operators-Hex evaluation and calculator with logica l and arithmetic operators
    2023-04-05 23:30:03下载
    积分:1
  • irbookonlinereading
    an introduction to information retrieval, great book for search engine in English
    2009-04-13 07:42:05下载
    积分:1
  • Test
    说明:  该模型是运用人工势场法进行的避障程序,障碍物包括一个动态障碍物和一个静态障碍物(The model is an obstacle avoidance program using artificial potential field method. The obstacles include a dynamic obstacle and a static obstacle)
    2021-04-27 13:48:45下载
    积分:1
  • good exsample about tree,great.implement in javascript.
    很好的关于树的例子,很不错。用javascript实现-good exsample about tree,great.implement in javascript.
    2022-02-06 13:45:24下载
    积分:1
  • 电调PWM输出调试
    说明:  使用STM32F407输出PWM,对电调进行校正和控制(Correction and Control of Electric Adjustment using STM32F407 output PWM,)
    2020-12-28 10:59:01下载
    积分:1
  • 115.2k serial port communication procedures and testing methods for the simple t...
    115.2k串行口通信程序,校验方式为简单双向校验,而且是必要的,因为任何采用中断、crc等的方法均很难保证速度和避免错误. 总体速度5KB/秒 -115.2k serial port communication procedures and testing methods for the simple two-way check, but is necessary, Any interrupt, crc the methods are difficult to ensure that the speed and avoid mistakes. the overall rate of 5 KB/sec
    2022-01-28 20:47:19下载
    积分:1
  • HT系列掌机与电脑通讯VB软件(含源码),支持以下系列的型号:HT1600,HT2680,HT2680A,HT28...
    HT系列掌机与电脑通讯VB软件(含源码),支持以下系列的型号:HT1600,HT2680,HT2680A,HT28-HT Series portable communications VB and computer software (including source code), to support the following series of model: HT1600, HT2680, HT2680A, HT2800
    2022-02-15 06:00:55下载
    积分:1
  • rsvd
    说明:  随机奇异值分解(一种快速奇异值分解的程序)(Stochastic singular value decomposition (program of fast singular value decomposition))
    2020-08-14 15:28:27下载
    积分:1
  • 696518资源总数
  • 106215会员总数
  • 5今日下载