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we propose a new activation function with parameters, named PATS. Specifically, PATS is a non-monotonic function which combines arctangent function and sigmoid function.

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NIN.py
NIN.py
 
 
README.md
README.md
 
 
dataset_10.py
dataset_10.py
 
 
dataset_100.py
dataset_100.py
 
 
densenet.py
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fig4-ab.py
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fig4-cd.py
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fig4-ef.py
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fig5-ab.py
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fig5-cd.py
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resnet_110.py
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resnet_20.py
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resnet_32.py
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resnet_50.py
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PATS: A New Neural Network Activation Function with Parameter

The project is used to test the PATS activation function. All network models are built in Python 3.6.7 environment based on Keras 2.2.4 neural network framework. Before running the code in the project, you need to download the cifar-10 / 100 dataset from http://www.cs.toronto.edu/~kriz/cifar.html

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we propose a new activation function with parameters, named PATS. Specifically, PATS is a non-monotonic function which combines arctangent function and sigmoid function.

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