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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التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	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.
التنسيق:	Статья
اللغة:	English
منشور في:	2023
الموضوعات:	Artificial neural networks Wavelets Convolution Correlation Feature vector Orthogonal transformations
الوصول للمادة أونلاين:	https://dspace.ncfu.ru/handle/20.500.12258/25214
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

الوصف
الملخص:	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.

Analysis of Neural Networks for Image Classification

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