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  • Open Access

    ARTICLE

    Activation Functions Effect on Fractal Coding Using Neural Networks

    Rashad A. Al-Jawfi*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 957-965, 2023, DOI:10.32604/iasc.2023.031700 - 29 September 2022

    Abstract Activation functions play an essential role in converting the output of the artificial neural network into nonlinear results, since without this nonlinearity, the results of the network will be less accurate. Nonlinearity is the mission of all nonlinear functions, except for polynomials. The activation function must be differentiable for backpropagation learning. This study’s objective is to determine the best activation functions for the approximation of each fractal image. Different results have been attained using Matlab and Visual Basic programs, which indicate that the bounded function is more helpful than other functions. The non-linearity of the… More >

  • Open Access

    ARTICLE

    Three-Dimensional Modeling of the Retinal Vascular Tree via Fractal Interpolation

    Hichem Guedri1,*, Abdullah Bajahzar2, Hafedh Belmabrouk3

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 59-77, 2021, DOI:10.32604/cmes.2021.013632 - 30 March 2021

    Abstract In recent years, the three dimensional reconstruction of vascular structures in the field of medical research has been extensively developed. Several studies describe the various numerical methods to numerical modeling of vascular structures in near-reality. However, the current approaches remain too expensive in terms of storage capacity. Therefore, it is necessary to find the right balance between the relevance of information and storage space. This article adopts two sets of human retinal blood vessel data in 3D to proceed with data reduction in the first part and then via 3D fractal reconstruction, recreate them in More >

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