VISUALIZATION METHODS OF IMAGE CLASSIFICATION PROCESS IN NEURAL NETWORKS

Authors

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

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

Chae Y.T., Horesh R., Hwang Y., Lee Y.M., Artificial neural network model for forecasting sub-hourly electricity usage in commercial buildings. [Piekļuve:12.04.2020]

Huang M., Hung Y., Lee W., Li R. K., Wang T.. Usage of Case-Based Reasoning, Neural Network and Adaptive Neuro-Fuzzy Inference System Classification Techniques in Breast Cancer Dataset Classification Diagnosis [Piekļuve:14.04.2020]

Kagaya H., Aizawa K. , Ogawa M. . Food Detection and Recognition Using Convolutional Neural Network. [Piekļuve:12.04.2020]

Zhang, H., Zou, Z., Li, J. et al. Flame image recognition of alumina rotary kiln by artificial neural network and support vector machine methods. J. Cent. South Univ. Technol. 15, 39–43 (2008). [Piekļuve:14.04.2020]

Sinha P. A symmetry perceiving adaptive neural network and facial image recognition [Piekļuve:14.04.2020]

VGG16 – Convolutional Network for Classification and Detection [Tiešsaiste] Pieejams: https://neurohive.io/en/popular-networks/vgg16/

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Published

2020-04-22

Issue

Section

Information Technologies