Integrating YOLOv8-based disaster detection with deep reinforcement learning for closed-loop UAV emergency response scheduling: A simulation study.
- DOI
- 10.1371/journal.pone.0361374
- Published
- 2026
- Container
- PloS one
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0361374,
title = {Integrating YOLOv8-based disaster detection with deep reinforcement learning for closed-loop UAV emergency response scheduling: A simulation study.},
author = {Zhang C and He R},
year = {2026},
journal = {PloS one},
doi = {10.1371/journal.pone.0361374},
url = {https://doi.org/10.1371/journal.pone.0361374}
}RIS
TY - JOUR TI - Integrating YOLOv8-based disaster detection with deep reinforcement learning for closed-loop UAV emergency response scheduling: A simulation study. AU - Zhang C AU - He R PY - 2026 JO - PloS one DO - 10.1371/journal.pone.0361374 UR - https://doi.org/10.1371/journal.pone.0361374 ER -
APA
C, Z., & R, H. (2026). Integrating YOLOv8-based disaster detection with deep reinforcement learning for closed-loop UAV emergency response scheduling: A simulation study.. PloS one. https://doi.org/10.1371/journal.pone.0361374
Source records
- pubmed · retrieved 2026-11-10T10:24:11.331Z