March 3, 2026

FFDNet: An End-to-End Lightweight Real-Time Fire Detection Model for Forest Fire Environments

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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