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Analysis of Neural Networks for Image Classification

Analysis of Neural Networks for Image Classification

The article explores the option of using information theory’s mathematical tools to model artificial neural networks. The two primary network architectures for image recognition, classification, and clustering are the feedforward network and convolutional networks. The study investigates the use of...

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Главные авторы: Vershkov, N. A., Вершков, Н. А., Babenko, M. G., Бабенко, М. Г., Kuchukov, V. A., Кучуков, В. А., Kuchukova, N. N., Кучукова, Н. Н., Kucherov, N. N., Кучеров, Н. Н.
格式: Статья
語言:English
出版: 2023
主題:
Artificial neural networks
Wavelets
Convolution
Correlation
Feature vector
Orthogonal transformations
在線閱讀:https://dspace.ncfu.ru/handle/20.500.12258/25214
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總結:The article explores the option of using information theory’s mathematical tools to model artificial neural networks. The two primary network architectures for image recognition, classification, and clustering are the feedforward network and convolutional networks. The study investigates the use of orthogonal transformations to enhance the effectiveness of neural networks and wavelet transforms in convolutional networks. The research proposes practical applications based on the theoretical findings.

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