| Autor: |
Stadnik Alexey V., Sazhin Pavel S., Hnatic Slavomir |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
EPJ Web of Conferences, Vol 226, p 02020 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2100-014X |
| DOI: |
10.1051/epjconf/202022602020 |
| Popis: |
The performance of neural networks is one of the most important topics in the field of computer vision. In this work, we analyze the speed of object detection using the well-known YOLOv3 neural network architecture in different frameworks under different hardware requirements. We obtain results, which allow us to formulate preliminary qualitative conclusions about the feasibility of various hardware scenarios to solve tasks in real-time environments. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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