Forest fires are one of the world's deadliest natural disasters. Early detection of forest fires
can help minimize the damage to ecosystems and forest life. In this paper, we propose an …

Aiming at the problem that the existing target detection algorithms are difficult to detect
sudden fire with high precision in real-time in the complex forest environment, an improved …

Forest is an important resource for human survival, and forest fires are a serious threat to
forest protection. Therefore, the early detection of fire and smoke is particularly important …

Traditional forest fire detection based on sensing devices has a small range, low sensitivity
and high false alarm rate, while existing forest fire detection methods based on deep …

Accidental fire outbreak threatens people's life and property safety, and it is of great
significance to study fire detection and alarm early. The detection range of traditional fire …

Intense, large-scale forest fires are damaging and very challenging to control. Locations,
where various types of fire behavior occur, vary depending on environmental factors …

For the detection of fire-like targets in indoor, outdoor and forest fire images, as well as fire
detection under different natural lights, an improved YOLOv5 fire detection deep learning …

Early fire detection is quite important to fighting of forest fire. A lightweight YOLO forest fire
detection model is proposed in this study. First, the YOLOv4 object detection model is …

Accurate monitoring of fire and smoke plays an irreplaceable role in preventing fires and
safeguarding the safety of citizens' lives and property. The network structure of YOLOv5 is …

Forest fires are highly unpredictable and extremely destructive. Traditional methods of
manual inspection, sensor-based detection, satellite remote sensing and computer vision …