Fire YOLOv5 Attains

Fire YOLOv5 Attains refers to the application and optimization of the YOLOv5 object detection model for fire detection in various contexts, including forests, kitchens, and other environments. Current research focuses on improving YOLOv5's accuracy and efficiency in detecting small fires and smoke, often through architectural modifications like adding attention mechanisms or specialized prediction heads, and comparing its performance against other YOLO versions (e.g., YOLOv8, YOLOv10). This work is significant for enhancing real-time fire detection capabilities in safety and surveillance systems, contributing to improved response times and potentially reducing fire-related damage.