| Autor: |
Gyu Seon Kim, Haemin Lee, Soohyun Park, Joongheon Kim |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
ETRI Journal, Vol 45, Iss 5, Pp 811-821 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1225-6463 |
| DOI: |
10.4218/etrij.2023-0121 |
| Popis: |
We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore, we introduce a self-adaptive control strategy to maximize the time-averaged recognition performance subject to stability through a formulation based on Lyapunov optimization. Results from performance evaluations on real-world data demonstrate that the proposed algorithm achieves the desired performance improvements. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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