TY  - EJOU
AU  - Enomoto, Tomoyuki 
AU  - Kakuda, Kazuhiko 
AU  - Miura, Shinichiro 

TI  - New Activation Functions in CNN and Its Applications
T2  - The International Conference on Computational \& Experimental Engineering and Sciences

PY  - 2019
VL  - 21
IS  - 2
SN  - 1933-2815

AB  - In this paper, the nonlinear activation functions based on fluid dynamics are presented. We propose two types of activation functions by applying the so-called parametric softsign to the negative region. We apply the activation function to CNN (Convolutional Neural Network) which performs image recognition and approaches from multiple benchmark datasets such as MNIST, CIFAR-10. Numerical results demonstrate the workability and the validity of the present approach through comparison with other numerical performances.
KW  - Deep learning
KW  -  CNN
KW  -  activation function
KW  -  fluid dynamics
KW  -  CIFAR-10

DO  - 10.32604/icces.2019.05292