Open AccessDesigning architecture of an artificial neural network for classification using robotic complexes
Author(s) -
Ksenia Konko,
D. G. Demidov,
Aleksey Vinokur,
В. Л. Крупенин
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/747/1/012116
Subject(s) - convolutional neural network , artificial intelligence , computer science , artificial neural network , architecture , raster graphics , deep learning , time delay neural network , machine learning , pattern recognition (psychology) , art , visual arts
This article describes the basic principles of constructing artificial neural networks for pattern recognition on raster images using robotic complexes. The basic parts of convolutional neural networks are considered. Examples of evaluating the accuracy of preliminary testing results developed by the authors of a convolutional neural network model are given.