| Title | Analysis of Subject Recognition Algorithms based on Neural Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Tashev, Komil, Rustamova, Sanobar |
| Conference Name | 2020 International Conference on Information Science and Communications Technologies (ICISCT) |
| Date Published | Nov. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-9969-6 |
| Keywords | artificial neural network, Artificial neural networks, Collaboration, composability, cryptology, Human Behavior, human factors, information science, Metrics, Pattern recognition, pubcrawl, resilience, resilient, Scalability, simplest perceptron, Software, Software algorithms, Task Analysis, Text recognition, Training |
| Abstract | This article describes the principles of construction, training and use of neural networks. The features of the neural network approach are indicated, as well as the range of tasks for which it is most preferable. Algorithms of functioning, software implementation and results of work of an artificial neural network are presented. |
| URL | https://ieeexplore.ieee.org/document/9351414 |
| DOI | 10.1109/ICISCT50599.2020.9351414 |
| Citation Key | tashev_analysis_2020 |
Analysis of Subject Recognition Algorithms based on Neural Networks