Using Convolutional Neural Networks for the Analysis of Nonstationary Signals on the Problem Diagnostics Vision Pathologies

Author:

Eremeev Alexander,Ivliev Sergey

Publisher

Springer International Publishing

Reference10 articles.

1. Anisimov, D.N., Vershinin, D.V., Kolosov, O.S., Zueva, M.V., Tsapenko, I.V.: Diagnostics of the current state of dynamic objects and systems of complex structure using fuzzy logic methods using imitation models. Artificial Intelligence and Decision Making, no. 3, pp. 39–50 (2012). (In Russian)

2. Eremeev, A.P., Ivliev, S.A.: Analysis and diagnostics of complex pathologies of vision based on wavelet transformations and the neural network approach. In: Collection of Scientific Proceedings of the VIII International Scientific and Technical Conference, Integrated Models and Soft Computing in Artificial Intelligence, Kolomna, 18–20 May 2015, pp. 589–595. Fizmatlit, Moscow (2015). (In Russian)

3. Kurysheva, N.I.: Maslova EV electrophysiological studies in the diagnosis of glaucoma. Natl. J. Glaucoma 16(1), 102–113 (2017). (In Russian)

4. Brynolfsson, J., Sandsten, M.: Classification of one-dimensional non-stationary signals using the Wigner-Ville distribution in convolutional neural networks. In: 25th European Signal Processing Conference, EUSIPCO 2017, pp. 326–330. Institute of Electrical and Electronics Engineers Inc. (2017). https://doi.org/10.23919/EUSIPCO.2017.8081222

5. Davies, E.R.: Computer Vision Principles, Algorithms, Applications, Learning, 5th edn, pp. 453–493. Academic Press, London (2018)

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