Tomoyuki Enomoto, Kazuhiko Kakuda, Shinichiro Miura
The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.2, pp. 36-39, 2019, DOI:10.32604/icces.2019.05292
Abstract 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. More >
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