登录
首页 » matlab » GAN-Base-on-Matlab-master

GAN-Base-on-Matlab-master

于 2019-01-09 发布
0 189
下载积分: 1 下载次数: 21
我要下载

代码说明：

说明：  生成手写数字图片，一共提供了三种算法，example_1和example_2训练GAN来生成手写数字图片，搭建了一个简单的GAN的网络结构，example_3难度较大(There are three algorithms to generate handwritten digital pictures. Example_1 and example_2 train GAN to generate handwritten digital pictures, and build a simple network structure of GAN. Example_3 is more difficult.)

文件列表：

GAN-Base-on-Matlab-master, 0 , 2018-12-12
GAN-Base-on-Matlab-master\.gitignore, 5 , 2018-12-12
GAN-Base-on-Matlab-master\LICENSE, 1350 , 2018-12-12
GAN-Base-on-Matlab-master\README.md, 2762 , 2018-12-12
GAN-Base-on-Matlab-master\activation, 0 , 2018-12-12
GAN-Base-on-Matlab-master\activation\activate_z.m, 472 , 2018-12-12
GAN-Base-on-Matlab-master\activation\delta_activation_function.m, 559 , 2018-12-12
GAN-Base-on-Matlab-master\activation\delta_leaky_relu.m, 157 , 2018-12-12
GAN-Base-on-Matlab-master\activation\delta_relu.m, 144 , 2018-12-12
GAN-Base-on-Matlab-master\activation\delta_sigmoid.m, 213 , 2018-12-12
GAN-Base-on-Matlab-master\activation\delta_tanh.m, 67 , 2018-12-12
GAN-Base-on-Matlab-master\activation\leaky_relu.m, 169 , 2018-12-12
GAN-Base-on-Matlab-master\activation\relu.m, 83 , 2018-12-12
GAN-Base-on-Matlab-master\activation\sigmoid.m, 60 , 2018-12-12
GAN-Base-on-Matlab-master\error_term, 0 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\delta_sigmoid_cross_entropy.m, 694 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\get_error_term_from_atrous_conv2d_layer.m, 554 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\get_error_term_from_batch_norm_layer.m, 1441 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\get_error_term_from_conv2d_layer.m, 554 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\get_error_term_from_conv2d_transpose_layer.m, 1936 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\get_error_term_from_fully_connect_layer.m, 121 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\get_error_term_from_reshape_layer.m, 137 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\get_error_term_from_sub_sampling_layer.m, 374 , 2018-12-12
GAN-Base-on-Matlab-master\error_term\sigmoid_cross_entropy.m, 284 , 2018-12-12
GAN-Base-on-Matlab-master\example_1.m, 1582 , 2018-12-12
GAN-Base-on-Matlab-master\example_2.m, 1144 , 2018-12-12
GAN-Base-on-Matlab-master\example_3.m, 1277 , 2018-12-12
GAN-Base-on-Matlab-master\gan_train.m, 2922 , 2018-12-12
GAN-Base-on-Matlab-master\gradient, 0 , 2018-12-12
GAN-Base-on-Matlab-master\gradient\calculate_gradient_for_atrous_conv2d_layer.m, 773 , 2018-12-12
GAN-Base-on-Matlab-master\gradient\calculate_gradient_for_batch_norm_layer.m, 731 , 2018-12-12
GAN-Base-on-Matlab-master\gradient\calculate_gradient_for_conv2d_layer.m, 739 , 2018-12-12
GAN-Base-on-Matlab-master\gradient\calculate_gradient_for_conv2d_transpose_layer.m, 1260 , 2018-12-12
GAN-Base-on-Matlab-master\gradient\calculate_gradient_for_fully_connect_layer.m, 179 , 2018-12-12
GAN-Base-on-Matlab-master\layer, 0 , 2018-12-12
GAN-Base-on-Matlab-master\layer\atrous_conv2d.m, 893 , 2018-12-12
GAN-Base-on-Matlab-master\layer\batch_norm.m, 1074 , 2018-12-12
GAN-Base-on-Matlab-master\layer\check_layer_field_names.m, 579 , 2018-12-12
GAN-Base-on-Matlab-master\layer\conv2d.m, 1062 , 2018-12-12
GAN-Base-on-Matlab-master\layer\conv2d_transpose.m, 1933 , 2018-12-12
GAN-Base-on-Matlab-master\layer\reshape_operation.m, 300 , 2018-12-12
GAN-Base-on-Matlab-master\layer\setup_atrous_conv2d_layer.m, 1631 , 2018-12-12
GAN-Base-on-Matlab-master\layer\setup_batch_norm_layer.m, 751 , 2018-12-12
GAN-Base-on-Matlab-master\layer\setup_conv2d_layer.m, 1594 , 2018-12-12
GAN-Base-on-Matlab-master\layer\setup_conv2d_transpose_layer.m, 5976 , 2018-12-12
GAN-Base-on-Matlab-master\layer\setup_fully_connect_layer.m, 704 , 2018-12-12
GAN-Base-on-Matlab-master\layer\setup_reshape_layer.m, 454 , 2018-12-12
GAN-Base-on-Matlab-master\layer\setup_sub_sampling_layer.m, 389 , 2018-12-12
GAN-Base-on-Matlab-master\layer\sub_sample.m, 346 , 2018-12-12
GAN-Base-on-Matlab-master\nerual_network_flow, 0 , 2018-12-12
GAN-Base-on-Matlab-master\nerual_network_flow\nn_applygrads_adam.m, 1408 , 2018-12-12
GAN-Base-on-Matlab-master\nerual_network_flow\nn_applygrads_sgd.m, 602 , 2018-12-12
GAN-Base-on-Matlab-master\nerual_network_flow\nn_bp_d.m, 2904 , 2018-12-12
GAN-Base-on-Matlab-master\nerual_network_flow\nn_bp_g.m, 2981 , 2018-12-12
GAN-Base-on-Matlab-master\nerual_network_flow\nn_ff.m, 1633 , 2018-12-12
GAN-Base-on-Matlab-master\nerual_network_flow\nn_setup.m, 1157 , 2018-12-12
GAN-Base-on-Matlab-master\readme_images, 0 , 2018-12-12
GAN-Base-on-Matlab-master\readme_images\1.png, 3660 , 2018-12-12
GAN-Base-on-Matlab-master\readme_images\2.png, 3589 , 2018-12-12
GAN-Base-on-Matlab-master\readme_images\3.png, 4283 , 2018-12-12
GAN-Base-on-Matlab-master\setup_environment.m, 296 , 2018-12-12
GAN-Base-on-Matlab-master\test, 0 , 2018-12-12
GAN-Base-on-Matlab-master\test\convolution_process.m, 1821 , 2018-12-12
GAN-Base-on-Matlab-master\util, 0 , 2018-12-12
GAN-Base-on-Matlab-master\util\argparse.m, 259 , 2018-12-12
GAN-Base-on-Matlab-master\util\expand.m, 1958 , 2018-12-12
GAN-Base-on-Matlab-master\util\flipall.m, 77 , 2018-12-12
GAN-Base-on-Matlab-master\util\insert_zeros_into_array.m, 329 , 2018-12-12
GAN-Base-on-Matlab-master\util\padding_height_width_in_array.m, 476 , 2018-12-12
GAN-Base-on-Matlab-master\util\save_images.m, 623 , 2018-12-12

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

  • as
    说明：  这是我们数字图像处理课程的大作业，我自己用matlabGUI做了一个界面，希望对大家有用，谢谢！(This is a large digital image processing program operations, for my own use matlabGUI made an interface and hope for all of us, thank you!)
    2009-09-16 20:07:46下载
    积分：1
  • canny
    canny边缘检测的步骤： 1，生成高斯核，与图像做卷积 2，计算梯度图像 3，非极大值抑制 4，双阈值法和连接边缘(Canny edge detection steps: 1, Generate Gaussian kernel, convolution with the image 2, calculate the gradient image 3, non-maximal inhibition 4, double threshold method and connect the edge)
    2017-11-28 19:31:27下载
    积分：1
  • ssim_index
    基于相似度的图像质量评价算法Structural SIMilarity (SSIM) index的实现。(This is an implementation of the algorithm for calculating the Structural SIMilarity (SSIM) index between two images. Please refer to the following paper: Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity" IEEE Transactios on Image Processing, vol. 13, no. 4, pp.600-612, )
    2009-06-06 17:19:40下载
    积分：1
  • InSAR_unwarping
    InSAR相位解缠用，好多种方法，参考或者改进其中的算法用(InSAR phase unwrapping, and a good variety of methods, reference, or to improve the algorithm by which)
    2021-02-19 10:49:44下载
    积分：1
  • 1
    说明：  这是一个利用python里微信机器人，然后获取微信好友的照片，然后利用图像处理，把照片合成在一张照片里。(This is a use of the python Weixin robot, and then get the pictures of Weixin friends, and then use image processing to synthesize the pictures in a picture.)
    2019-05-26 17:42:23下载
    积分：1
  • LightCompensate
    光照补偿matlab程序，很好很强大，很有效果(Illumination compensation matlab program)
    2012-05-29 08:24:50下载
    积分：1
  • chaos_logistic
    在产生混沌伪随机序列的混沌映射中，Logistic映射(Logistic Map)是一种简单而经典的映射。其中u称为分形参数，随着u逐渐增大，出现倍周期分岔现象。可用于密文域图像加密。(Logistic Map is a simple and classical mapping for generating chaotic pseudo-random sequences. U is called fractal parameter, and with the increase of u, period doubling bifurcation occurs. It can be used for image encryption in ciphertext domain.)
    2019-03-03 17:07:52下载
    积分：1
  • rr
    说明：  基于LBP纹理特征的运动目标检测算法.rar(Moving target detection algorithm based on LBP texture features. Rar)
    2013-01-03 12:21:30下载
    积分：1
  • root
    动态跟踪，边移动边绘制路线。规定经纬度的范围，调用地图的路径算法，求出路径。(Dynamic tracking, while moving to draw lines.Specified range of latitude and longitude, map the path algorithm call, find the path.)
    2014-01-15 15:09:51下载
    积分：1
  • FBP
    CT（computer tomography ）图像重建算法，FBP，是目前商用CT的主流重建算法(computer tomography reconstruction algrithm)
    2020-09-05 04:38:06下载
    积分：1
  • 696518资源总数
  • 106222会员总数
  • 14今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2025 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！