.idea
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1f26f95c7c
add LeNet5 cnn structure, conv, polling, dropout. cnn must be trained in a better GPU
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5 年之前 |
Encapsulation
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56ebfc2536
keras usage and other hight level apis
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5 年之前 |
LeNet5
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56ebfc2536
keras usage and other hight level apis
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5 年之前 |
MNIST_data
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20c7ffabb3
squeeze file structure
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6 年之前 |
RNN
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b73da0e7c4
tensorboard usage. RNN structure
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5 年之前 |
TF_Init
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4f40fbb383
some notes for the TF installation
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6 年之前 |
img_proc
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b73da0e7c4
tensorboard usage. RNN structure
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5 年之前 |
inceptionv3
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acbb23da1d
inceptionv3 nn structure, img_proccess, tfrecord read & write, multiThread, coordinator and queueRunner
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5 年之前 |
mnist_number_recognition
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1f26f95c7c
add LeNet5 cnn structure, conv, polling, dropout. cnn must be trained in a better GPU
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5 年之前 |
mnist_restructured
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1f26f95c7c
add LeNet5 cnn structure, conv, polling, dropout. cnn must be trained in a better GPU
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5 年之前 |
tests
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30ef1bf358
restructured nn for mnist number recognition, together with saved nn weights, diagrams and photos
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6 年之前 |
.gitignore
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448ad3851d
implement LeNet5 structure using dataset read from tfrecord. code debug. image sometimes stored as uint8 or float32, which need to be clear in mind when using the dataset. Some image preprocessing functions may require 3 channels image rather than grayscale image, such as modify saturation, hue and contrast.
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5 年之前 |
LICENSE
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591b2bde87
Initial commit
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6 年之前 |
README.md
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591b2bde87
Initial commit
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6 年之前 |
__init__.py
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448ad3851d
implement LeNet5 structure using dataset read from tfrecord. code debug. image sometimes stored as uint8 or float32, which need to be clear in mind when using the dataset. Some image preprocessing functions may require 3 channels image rather than grayscale image, such as modify saturation, hue and contrast.
|
5 年之前 |