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...
Gorde:
| Egile Nagusiak: | , , , , , , , , , |
|---|---|
| Formatua: | Статья |
| Hizkuntza: | English |
| Argitaratua: |
2023
|
| Gaiak: | |
| Sarrera elektronikoa: | https://dspace.ncfu.ru/handle/20.500.12258/25214 |
| Etiketak: |
Etiketa erantsi
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
|
| Gaia: | 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. |
|---|