Multi-Unmanned-Aerial-Vehicle Wildfire Boundary Estimation Using a Semantic Segmentation Neural Network-Reference-Cited by-同舟云学术

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Multi-Unmanned-Aerial-Vehicle Wildfire Boundary Estimation Using a Semantic Segmentation Neural Network

Published:2021-05 Issue:5 Volume:18 Page:231-249
ISSN:2327-3097
Container-title:Journal of Aerospace Information Systems
language:en
Short-container-title:Journal of Aerospace Information Systems

Author:

Castagno Jeremy¹,Romano Matthew¹,Kuevor Prince¹,Atkins Ella¹

Affiliation:

1. University of Michigan, Ann Arbor, Michigan 48109

Funder

National Science Foundation

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Aerospace Engineering

Link

https://arc.aiaa.org/doi/am-pdf/10.2514/1.I010912

Reference30 articles.

1. Polylidar - Polygons From Triangular Meshes

2. Consensus-Based Decentralized Auctions for Robust Task Allocation

3. A cooperative perception system for multiple UAVs: Application to automatic detection of forest fires

4. Low-cost Multi-UAV Technologies for Contour Mapping of Nuclear Radiation Field

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing Resolution and Fault Tolerance of Barrier Coverage with Unmanned Aerial Vehicles;Journal of Aerospace Information Systems;2024-06

2. WIT-UAS: A Wildland-Fire Infrared Thermal Dataset to Detect Crew Assets from Aerial Views;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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