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MNIST with TensorFlow-Slim

A Convolutional neural network for recognizing hand written digits. The script uses Matplotlib for visualizing layers, output, loss and accuracy.


Model:

Input - 28 x 28

Convolutional layer - 28 x 28 filters: 24

Max pooling layer - 14 x 14

Convolutional layer - 14 x 14 filters: 200

Max pooling layer - 7 x 7

Convolutional layer - 7 x 7 filters: 20

Dropout layer - 0.8

Fully connected layer - 10 outputs (Softmax)


Layer outputs:

Test accuracy in this case: 0.985614:


Few epochs and similar digits can result in bigger uncertainty:

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TF-Slim MNIST classification with layer visualization.

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