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Keras-MNIST-center-loss-with-visualization

Fig. (left) Softmax only. (right) Softmax with center loss

Update (2018/03/02)

Update (2017/11/10)

  • Remove the one-hot inputs for Embedding layer and replace it by single value labels.
  • There are two kinds labels: single value for center loss, and one-hot vector labels for softmax term.
  • Every classes are visually seperated now :)

How to run?

  • Step.1 Change the flag of center loss inside TYY_mnist.py
isCenterloss = True
#isCenterloss = False
  • Step.2 Run the file
KERAS_BACKEND=tensorflow python TYY_mnist.py

Dependencies

  • Anaconda
  • Keras
  • Tensorflow
  • Others: (install with anaconda)
conda install -c anaconda scikit-learn 
conda install -c conda-forge matplotlib

References:

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