The Duo of Visual Servoing and Deep Learning-Based Methods for Situation-Aware Disaster Management: A Comprehensive Review
Author:
Funder
King Saud University
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12559-024-10290-4.pdf
Reference137 articles.
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2. Sendai Framework for Disaster Risk Reduction 2015-2030 — undrr.org. 2015. https://www.undrr.org/publication/sendai-framework-disaster-risk-reduction-2015-2030. Accessed 26 Aug 2023.
3. Cui F. Deployment and integration of smart sensors with IoT devices detecting fire disasters in huge forest environment. Comput Commun. 2020;150:818–27.
4. Hildmann H, Kovacs E. Using unmanned aerial vehicles (UAVs) as mobile sensing platforms (MSPS) for disaster response, civil security and public safety. Drones. 2019;3(3):59.
5. Machkour Z, Ortiz-Arroyo D, Durdevic P. Classical and deep learning based visual servoing systems: a survey on state of the art. J Intell Robot Syst. 2022;104(1):1–27.
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