Application of Modular Neural Networks for Image Recognition in Foggy Computing Environments

Authors

  • Natalia Kuchukova North-Caucasus Federal University, Stavropol, Russia
  • Nikolay Vershkov North-Caucasus Federal University, Stavropol, Russia

DOI:

https://doi.org/10.25728/assa.2025.2025.1.1666

Keywords:

artificial neural network, image recognition, fog computing, wavelet transform, proportional division of layers of the neural network

Abstract

The paper considers various approaches to the decomposition of artificial neural networks for the purpose of their application on fog computing nodes. Based on the requirements for the organization of fog computing, a method of dividing the input information into subspaces by means of wavelet transform and subsequent proportional division of all layers of the neural network is proposed. The proposed approach achieves a significant gain in the amount of information transferred between modules compared to the currently used layer-by-layer partitioning. In addition, the proposed method optimizes the load on fog computing nodes by partially utilizing the modules.

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Published

2025-08-24

How to Cite

Application of Modular Neural Networks for Image Recognition in Foggy Computing Environments. (2025). Advances in Systems Science and Applications, 2025(1), 22-29. https://doi.org/10.25728/assa.2025.2025.1.1666