Fine-Grained Forest Fire Image Recognition Algorithm for UAV Aerial Photography Based on Dynamic Threshold Adaptive Attention Mechanism

Purpose: This study addresses critical challenges in fine-grained forest fire recognition from UAV aerial photography by developing a dynamic threshold adaptive attention mechanism capable of real-time environmental adaptation and multi-scale fire signature detection across varying conditions. Methodology:The proposed framework integrates three core components: dynamic threshold determination module, adaptive attention weight calculation system, and hierarchical feature fusion network.The algorithm employs real-time analysis of local image statistics and environmental parameters to adaptively adjust detection sensitivity.Comprehensive evaluation was conducted on three benchmark datasets (FLAME, FIgLib, VisiFire) using standard object detection metrics and computational efficiency