Premium
Proposal of New Activation Function in Deep Image Prior
Author(s) -
Segawa Ryo,
Hayashi Hitoshi,
Fujii Shohei
Publication year - 2020
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.23191
Subject(s) - image (mathematics) , activation function , function (biology) , value (mathematics) , artificial intelligence , computer science , algorithm , machine learning , artificial neural network , evolutionary biology , biology
We propose a new activation function and verify its performance in a deep image prior network. The new activation function is RSwish, which is Swish with a random slope for x < 0 assuming that the input value of the activation function is x . In addition, we manipulate the probability of the random number and observe the effect. As a result, we found that RSwish can perform better than Swish by manipulating probabilities according to the degree of color change in the image. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.