Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12258/19612
Title: Neural network analysis for image classification
Authors: Vershkov, N. A.
Вершков, Н. А.
Babenko, M. G.
Бабенко, М. Г.
Kuchukov, V. A.
Кучуков, В. А.
Kuchukova, N. N.
Кучукова, Н. Н.
Keywords: Convolutional neural networks;Neural networks;Sub-band coding;Sub-band filtering;Wave model
Issue Date: 2022
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Vershkov N. A., Babenko M. G., Kuchukov V. A., Kuchukova N. N. Neural network analysis for image classification // Lecture Notes in Networks and Systems. - 2022. - Том 424. - Стр.: 455 - 466. - DOI10.1007/978-3-030-97020-8_41
Series/Report no.: Lecture Notes in Networks and Systems
Abstract: The article considers the possibility of modeling artificial neural networks using the mathematical apparatus of information theory. The issues of pattern recognition, classification and clustering of images using neural networks are represented by two main architectures: a direct distribution network and convolutional networks. The possibility of using orthogonal transformations to increase the efficiency of neural networks, the use of wavelet transformations in convolutional networks is investigated. Based on the theoretical studies carried out, the directions on practical application of the obtained results are proposed.
URI: http://hdl.handle.net/20.500.12258/19612
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

Files in This Item:
File SizeFormat 
scopusresults 2180 .pdf
  Restricted Access
63.62 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.