VISUALIZATION METHODS OF IMAGE CLASSIFICATION PROCESS IN NEURAL NETWORKS

Authors

  • Kaspars Vogulis Rezekne Academy of Technologies (LV)
  • Valdis Platonovs Rezekne Academy of Technologies (LV)
  • Edgars Judovičs Rezekne Academy of Technologies (LV)
  • Sergejs Kodors Rezekne Academy of Technologies (LV)

DOI:

https://doi.org/10.17770/het2020.24.6760

Keywords:

image classification, neural networks, layers

Abstract

The aim of the work was to find and describe ways of visualising layers of neural netwoks, which analyse images and classify them. By visualising network layers, scientists and developers could see features, which influence on results of neural network mapping, training and overall result. In this paper, authors demonstrate different visualization methods, which can be applied by machine learning engineers.

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References

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Published

2020-04-22

Issue

Section

Information Technologies

How to Cite

[1]
K. Vogulis, V. Platonovs, E. Judovičs, and S. Kodors, “VISUALIZATION METHODS OF IMAGE CLASSIFICATION PROCESS IN NEURAL NETWORKS”, HET, no. 24, pp. 110–116, Apr. 2020, doi: 10.17770/het2020.24.6760.