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GAN-Base-on-Matlab-master

于 2019-01-09 发布
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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

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  • 652697
    获取系统进程信息源码，程序结合易语言模块斩月_图像相关模块.ec，调用API函数实现屏幕差异传输。(Get system processes information source , combined with easy language module program _ Zangetsu image correlation module .ec, call the API function screen difference transmission .)
    2016-10-26 00:42:37下载
    积分：1
  • RANSAC+SURF
    说明：  基于SURF算法实现图像特征提取与描述，使用RANSAC进行图像细配准(SURF algorithm was used to extract and describe image features, and RANSAC was used for image registration)
    2021-03-03 15:09:33下载
    积分：1
  • super-reserlution
    说明：  在一图像中加入噪声，是超分辨率中的一个重要步骤哦(noise)
    2010-03-25 19:00:08下载
    积分：1
  • Untitled
    将原图像进行退化处理（选择大气湍流导致图像模糊时相应的PSF），然后将退化后的图像进行复原（使用维纳滤波、直接逆滤波）.(The original image degradation process,and then restore the degraded image with Wiener filtering and inverse filtering.)
    2015-04-20 10:31:08下载
    积分：1
  • 改进svm
    说明：  phog方法提取图像特征，svm支持向量机进行分类，分别有GA遗传算法和PSO粒子群优化算法进行寻优。(Phog method extracted image features, SVM support vector machine classification, respectively, GA genetic algorithm and PSO particle swarm optimization algorithm for optimization.)
    2021-03-06 16:19:30下载
    积分：1
  • watermark_paper
    首先将二值水印图像经过降维操作转化为一维序列,再将一维序列与m 序列做扩频 调制,最后对音频信号进行分段离散余弦变换,把经过调制的水印信号经过量化处理过程嵌入到离 散余弦变换后的系数中 提取水印时对含水印信号的音频信号也进行分段离散余弦变换,然后利用 原始音频信号提取水印. 实验证明了该技术的鲁棒性和不可感知性.
    2020-12-06 20:19:22下载
    积分：1
  • 4
    说明：  我主要做的是图像分割算法的研究，这个是图像分割的程序，主要用神经网络！(I mainly do is to image segmentation algorithm, this is the image segmentation procedure, the main neural network!)
    2008-06-26 21:23:43下载
    积分：1
  • DieDai
    基于小波变换的利用阈值法迭代法的图像分割技术(Wavelet Segmentation of the iteration method)
    2012-04-28 20:43:48下载
    积分：1
  • texture_synthesis
    基于样本的纹理合成，采取点替换的方法，可以合成brodatz类的纹理。采取的方法是先对图像分析，然后合成。(Texture synthesis based on samples taken at the replacement of the method of texture synthesis brodatz category. Approach taken is to firstly image analysis, and then synthesis.)
    2007-12-03 21:29:06下载
    积分：1
  • patchwork_wangying
    利用matlab实现Patchwork算法，包括各种处理攻击(Using matlab Patchwork algorithm, including the attack of various treatment)
    2012-03-19 16:44:43下载
    积分：1
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