Collaborative forest fire identification: a lightweight model-based approach
Theory and Technology|更新时间:2026-10-10
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Collaborative forest fire identification: a lightweight model-based approach
Chinese Journal on Internet of ThingsVol. 10, Issue 2, Pages: 189-200(2026)
作者机构:
1.西安建筑科技大学信息与控制工程学院,陕西 西安 710399
2.陕西师范大学物理学与信息技术学院,陕西 西安 710119
3.南京邮电大学通信与信息工程学院,江苏 南京 210003
4.西安电子科技大学通信工程学院,陕西 西安 710071
作者简介:
基金信息:
The National Natural Science Foundation of China(61701365);Young Elite Scientists Sponsorship Program by CAST(2022QNRC001);Key Research and Development Program of Shaanxi Province(2025CY-YBXM-063);The Natural Science Basic Research Program of Shaanxi Province(2 025JC-YBMS-791)
Liu Runzi,Liu Chenwei,Wu Weihua,et al.Collaborative forest fire identification: a lightweight model-based approach[J].Chinese Journal on Internet of Things,2026,10(02):189-200.
Liu Runzi,Liu Chenwei,Wu Weihua,et al.Collaborative forest fire identification: a lightweight model-based approach[J].Chinese Journal on Internet of Things,2026,10(02):189-200.DOI: 10.11959/j.issn.2096-3750.WLW25113.
Collaborative forest fire identification: a lightweight model-based approach