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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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发表评论

0 个回复

  • hough
    基于OpenCV的hough变换检测图像直线,本代码能够识别焊缝跟踪功能。(OpenCV based hough transform to detect linear image, the code can identify seam tracking.)
    2013-11-08 16:04:26下载
    积分：1
  • WaterShed
    WaterShed图像分割方法，使用C++来编写的程序，分割效果还不错，不过要用的话，自己还是要调一下的。(WaterShed image segmentation method, using C++ to write programs, segmentation results were pretty good, but use the words that he is still would like to stress the.)
    2010-03-13 14:03:35下载
    积分：1
  • zhongxin
    经过一系列步骤实现结构光的中心提取，结果还不错(After a series of steps, the center of structured light is extracted, and the result is not bad.)
    2018-05-10 19:27:50下载
    积分：1
  • svm
    相当经典的一款SVM 可视化相当好，当今流行的2大SVM()
    2008-05-10 20:45:14下载
    积分：1
  • imageprocess
    图像处理方法的总汇，包含了滤波、灰度变换、对比度、亮度、二值等(The pool of image processing methods, including the filter, gray-scale transformation, contrast, brightness, and other binary)
    2009-06-09 08:58:13下载
    积分：1
  • M-Khook
    vc++编写的鼠标键盘消息的拦截程序，运用钩子实现(vc++ prepared to intercept mouse messages keyboard procedures, the use of hook realize)
    2008-04-13 16:41:55下载
    积分：1
  • program
    多种SAR成像的算法MATLAB程序，包括CS,RMA,RD(A variety of SAR imaging algorithm MATLAB program, including CS, RMA, RD)
    2020-06-30 07:40:02下载
    积分：1
  • pca
    说明：  这是用matlab编写的关于人脸识别的基于pca的完整程序，非常实用(This is prepared using matlab on pca-based face recognition of the integrity of the process, very useful)
    2009-08-23 09:43:20下载
    积分：1
  • 4
    说明：  扩散映射置乱与超混沌系统组合图像加密算法 扩散映射置乱与超混沌系统组合图像加密算法(Combi ned i mage encryption a lgor ithm ba sed on di ffusi on mapped disorder and hyperchaoti c system s)
    2009-11-15 11:15:47下载
    积分：1
  • bzoj
    随着这些年计算机硬件水平的发展, 计算速度的提高, 源自序列蒙特卡罗方法的蒙特卡罗粒子滤波方法的应用研究又重新活跃起来,本()
    2018-07-06 09:39:59下载
    积分：1
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