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FFDNet: An End-to-End Lightweight Real-Time Fire Detection Model for Forest Fire Environments | Synapse
March 3, 2026
FFDNet: An End-to-End Lightweight Real-Time Fire Detection Model for Forest Fire Environments
QY
Qian Yu
Central South University of Forestry and Technology
GZ
Gui Zhang
Central South University of Forestry and Technology
YW
Ying Wang
Central South University of Forestry and Technology
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Key Points
Fire detection accuracy is enhanced by using an end-to-end model that operates in real-time, effectively identifying forest fire threats.
The model achieves detection with a low false positive rate, ensuring reliability in various fire-prone environments.
Using lightweight architecture, the fire detection model remains efficient enough for deployment on devices with limited computational resources.
Implications of this model support proactive measures in forest fire prevention and management, especially in vulnerable areas.
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Yu et al. (Sun,) studied this question.
synapsesocial.com/papers/69a7617dc6e9836116a2f7ff
https://doi.org/https://doi.org/10.1016/j.pce.2026.104325
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