Haiwen Yin

Abstract Real-time fire detection and precise geographic localization using unmanned aerial vehicles (UAVs) are critical for early forest-fire warning. However, existing approaches face a fundamental dilemma: achieving high detection accuracy requires complex deep learning models with prohibitive computational costs, while lightweight models sacrifice localization precision due to the lack of spatial priors.