Year: 2025
Type: article
Abstract: This article presents a brief analysis and comparison of modern neural network architectures such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Transformers, and Graph Neural Networks (GNN). Their key features, advantages, and limitations are described. The article provides comparative analysis results based on recent publications and practical experiments.
Authors: Фаргиева, З.С., Котиева, П.Б.
Language: Russian
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7222863504