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TensorFlow-Examples-master

于 2018-04-01 发布 文件大小:2814KB
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代码说明：

  基于Tensorflow的Unet实现，里面有详细的教程。(TensorFlow for Unet, in which there are detailed teaching lecture.)

文件列表：

TensorFlow-Examples-master\.gitignore, 118 , 2018-03-07
TensorFlow-Examples-master\examples\1_Introduction\basic_eager_api.py, 1937 , 2018-03-15
TensorFlow-Examples-master\examples\1_Introduction\basic_operations.py, 2355 , 2018-03-07
TensorFlow-Examples-master\examples\1_Introduction\helloworld.py, 483 , 2018-03-15
TensorFlow-Examples-master\examples\2_BasicModels\kmeans.py, 3159 , 2018-03-07
TensorFlow-Examples-master\examples\2_BasicModels\linear_regression.py, 2986 , 2018-03-07
TensorFlow-Examples-master\examples\2_BasicModels\linear_regression_eager_api.py, 2043 , 2018-03-07
TensorFlow-Examples-master\examples\2_BasicModels\logistic_regression.py, 2360 , 2018-03-07
TensorFlow-Examples-master\examples\2_BasicModels\logistic_regression_eager_api.py, 3155 , 2018-03-07
TensorFlow-Examples-master\examples\2_BasicModels\nearest_neighbor.py, 1735 , 2018-03-15
TensorFlow-Examples-master\examples\2_BasicModels\random_forest.py, 2753 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\autoencoder.py, 4755 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\bidirectional_rnn.py, 4571 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\convolutional_network.py, 4759 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\convolutional_network_raw.py, 4814 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\dcgan.py, 6243 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\dynamic_rnn.py, 7373 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\gan.py, 5655 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\multilayer_perceptron.py, 3562 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\neural_network.py, 3413 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\neural_network_eager_api.py, 4221 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\neural_network_raw.py, 3384 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\recurrent_network.py, 3989 , 2018-03-07
TensorFlow-Examples-master\examples\3_NeuralNetworks\variational_autoencoder.py, 5319 , 2018-03-07
TensorFlow-Examples-master\examples\4_Utils\save_restore_model.py, 4859 , 2018-03-07
TensorFlow-Examples-master\examples\4_Utils\tensorboard_advanced.py, 5152 , 2018-03-07
TensorFlow-Examples-master\examples\4_Utils\tensorboard_basic.py, 3346 , 2018-03-07
TensorFlow-Examples-master\examples\5_DataManagement\build_an_image_dataset.py, 7397 , 2018-03-07
TensorFlow-Examples-master\examples\5_DataManagement\tensorflow_dataset_api.py, 5345 , 2018-03-07
TensorFlow-Examples-master\examples\6_MultiGPU\multigpu_basics.py, 2356 , 2018-03-07
TensorFlow-Examples-master\examples\6_MultiGPU\multigpu_cnn.py, 7873 , 2018-03-07
TensorFlow-Examples-master\input_data.py, 5709 , 2018-03-07
TensorFlow-Examples-master\LICENSE, 1386 , 2018-03-07
TensorFlow-Examples-master\notebooks\0_Prerequisite\ml_introduction.ipynb, 1914 , 2018-03-07
TensorFlow-Examples-master\notebooks\0_Prerequisite\mnist_dataset_intro.ipynb, 2622 , 2018-03-07
TensorFlow-Examples-master\notebooks\1_Introduction\basic_operations.ipynb, 5297 , 2018-03-07
TensorFlow-Examples-master\notebooks\1_Introduction\helloworld.ipynb, 1592 , 2018-03-07
TensorFlow-Examples-master\notebooks\2_BasicModels\kmeans.ipynb, 6364 , 2018-03-07
TensorFlow-Examples-master\notebooks\2_BasicModels\linear_regression.ipynb, 62033 , 2018-03-07
TensorFlow-Examples-master\notebooks\2_BasicModels\logistic_regression.ipynb, 5001 , 2018-03-07
TensorFlow-Examples-master\notebooks\2_BasicModels\nearest_neighbor.ipynb, 13095 , 2018-03-07
TensorFlow-Examples-master\notebooks\2_BasicModels\random_forest.ipynb, 7735 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\autoencoder.ipynb, 47239 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\bidirectional_rnn.ipynb, 11956 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\convolutional_network.ipynb, 33214 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\convolutional_network_raw.ipynb, 12114 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\dcgan.ipynb, 50310 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\dynamic_rnn.ipynb, 15134 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\gan.ipynb, 46898 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\neural_network.ipynb, 30679 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\neural_network_raw.ipynb, 7146 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\recurrent_network.ipynb, 11292 , 2018-03-07
TensorFlow-Examples-master\notebooks\3_NeuralNetworks\variational_autoencoder.ipynb, 298726 , 2018-03-07
TensorFlow-Examples-master\notebooks\4_Utils\save_restore_model.ipynb, 8471 , 2018-03-07
TensorFlow-Examples-master\notebooks\4_Utils\tensorboard_advanced.ipynb, 10238 , 2018-03-07
TensorFlow-Examples-master\notebooks\4_Utils\tensorboard_basic.ipynb, 6959 , 2018-03-07
TensorFlow-Examples-master\notebooks\5_DataManagement\build_an_image_dataset.ipynb, 10524 , 2018-03-07
TensorFlow-Examples-master\notebooks\5_DataManagement\tensorflow_dataset_api.ipynb, 8841 , 2018-03-07
TensorFlow-Examples-master\notebooks\6_MultiGPU\multigpu_basics.ipynb, 4385 , 2018-03-07
TensorFlow-Examples-master\notebooks\6_MultiGPU\multigpu_cnn.ipynb, 14411 , 2018-03-07
TensorFlow-Examples-master\README.md, 11953 , 2018-03-07
TensorFlow-Examples-master\resources\img\tensorboard_advanced_1.png, 286897 , 2018-03-07
TensorFlow-Examples-master\resources\img\tensorboard_advanced_2.png, 329796 , 2018-03-07
TensorFlow-Examples-master\resources\img\tensorboard_advanced_3.png, 1011024 , 2018-03-07
TensorFlow-Examples-master\resources\img\tensorboard_advanced_4.png, 607057 , 2018-03-07
TensorFlow-Examples-master\resources\img\tensorboard_basic_1.png, 284683 , 2018-03-07
TensorFlow-Examples-master\resources\img\tensorboard_basic_2.png, 349097 , 2018-03-07
TensorFlow-Examples-master\examples\1_Introduction, 0 , 2018-03-15
TensorFlow-Examples-master\examples\2_BasicModels, 0 , 2018-03-15
TensorFlow-Examples-master\examples\3_NeuralNetworks, 0 , 2018-03-15
TensorFlow-Examples-master\examples\4_Utils, 0 , 2018-03-15
TensorFlow-Examples-master\examples\5_DataManagement, 0 , 2018-03-15
TensorFlow-Examples-master\examples\6_MultiGPU, 0 , 2018-03-15
TensorFlow-Examples-master\notebooks\0_Prerequisite, 0 , 2018-03-15
TensorFlow-Examples-master\notebooks\1_Introduction, 0 , 2018-03-15
TensorFlow-Examples-master\notebooks\2_BasicModels, 0 , 2018-03-15
TensorFlow-Examples-master\notebooks\3_NeuralNetworks, 0 , 2018-03-15
TensorFlow-Examples-master\notebooks\4_Utils, 0 , 2018-03-15
TensorFlow-Examples-master\notebooks\5_DataManagement, 0 , 2018-03-15
TensorFlow-Examples-master\notebooks\6_MultiGPU, 0 , 2018-03-15
TensorFlow-Examples-master\resources\img, 0 , 2018-03-15
TensorFlow-Examples-master\examples, 0 , 2018-03-15
TensorFlow-Examples-master\notebooks, 0 , 2018-03-15
TensorFlow-Examples-master\resources, 0 , 2018-03-15
TensorFlow-Examples-master, 0 , 2018-03-15

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    说明：  Matlab实现简单图形处理，包括灰度、亮度、对比度变化等功能(Implement Simple Graphics Processing with matlab. Equipped with the function of gray level,brighteness and contrast ratio transfotmation.)
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    说明：  [屏幕抓字生成字库工具与找字函数]v5.6 By FeiYue 主要功能：快捷抓取、查找屏幕文字图像，生成的代码可用于AHK脚本。v5.6 改进：颜色模式增加了对偏色的支持，方便高手在游戏中使用。([screen grabbing to generate word library tool and word finding function] V5.6 by Feiyue Main functions: quickly grab and search the text image of the screen, and the generated code can be used for AHK script. V5.6 improvement: the color mode increases the support for color deviation, which is convenient for experts to use in the game.)
    2020-03-22 14:53:40下载
    积分：1
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    用于全息成像的算法，采用球面波照射物体，进行图像还原，代码可运行。(The algorithm for holographic imaging uses spherical wave to illuminate objects and restore images, so the code can run.)
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    使用vtk库开发的volume程序，主要用于建立多边形面片，用于演示三维体的算法。(Developed using VTK library volume procedures, set up primarily for polygon surfaces for the presentation of three-dimensional body algorithms.)
    2009-02-18 16:45:24下载
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    这是一个基于地震电磁时频图像的特征区域分割算法的程序(it is very good)
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