Пропуск в контексте
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...

全面介绍

Сохранить в:
书目详细资料
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
语言:English
出版: 2023
主题:
Artificial neural networks
Wavelets
Convolution
Correlation
Feature vector
Orthogonal transformations
在线阅读:https://dspace.ncfu.ru/handle/20.500.12258/25214
标签: 添加标签
没有标签, 成为第一个标记此记录!
实物特征
总结: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.

相似书籍