Efficiency Analysis of the Image Optimization Algorithm for the Formation of a Database Not Confirmed by the User

D.O. Zubariev, Post-graduate
G.E. Pukhov Institute for Modelling in Energy Engineering
National Academy of Sciences of Ukraine
(15, General Naumov Str., 03164, Kiev, Ukraine,
tel. +380996810567; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.),
I.S. Skarga-Bandurova, Doct. of Technical Sciences,
O.M. Sapytska, Cand. of Historical Sciences,
Volodymyr Dahl East Ukrainian National University
(59a, Tsentralny pr., 93400, Severodonetsk, Luhansk oblast, Ukraine,
tel. +380645228997; +380664838802;
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it.)

Èlektron. model. 2020, 42(2):59-68


The ultimate goal of any process optimization in a particular area is to save time and human resources. The article analyzes the effectiveness of the original algorithm image processing when sampling for training artificial neural network CNN Class based on User-Confirmed Image-Dataset for needs defining image elements within binary logic.


Deep learning, Image-Dataset, image optimization function, network learning algorithm.


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