Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access

    ARTICLE

    A Universal Activation Function for Deep Learning

    Seung-Yeon Hwang1, Jeong-Joon Kim2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3553-3569, 2023, DOI:10.32604/cmc.2023.037028 - 31 March 2023

    Abstract Recently, deep learning has achieved remarkable results in fields that require human cognitive ability, learning ability, and reasoning ability. Activation functions are very important because they provide the ability of artificial neural networks to learn complex patterns through nonlinearity. Various activation functions are being studied to solve problems such as vanishing gradients and dying nodes that may occur in the deep learning process. However, it takes a lot of time and effort for researchers to use the existing activation function in their research. Therefore, in this paper, we propose a universal activation function (UA) so… More >

Displaying 1-10 on page 1 of 1. Per Page