“Early forest fire detection methods can detect fires early and buy valuable time for rescue work. Researchers proposed an EFFNet model that integrates visible light and thermal infrared dual modes, achieving 97.2% detection accuracy on the RGBT-3M dataset with only 1.84M parameters, providing a lightweight solution for real-time monitoring of forest fires by unmanned aerial vehicles.”