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 …

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 …

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 …

Fire is a serious disaster that endangers life and property worldwide. Accurate and prompt
fire detection can provide early warning information for firefighting efforts. Deep learning …

Fire is a major disaster in the world, and the fire detection system should accurately detect
the fire in the shortest time to reduce economic loss and ecological damage. Traditional …

Fire detection and alarm system is fully concerned for safety. And convolutional neural
network (CNN) has been introduced into fire/smoke detection based on video/image …

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

Forest fire detection is a challenging problem in computer vision. In this paper, we build a
challenging fire dataset which contains images of fire, smoke, and red leaf to better simulate …

It is well-established that contact fire sensors are susceptible to interference from non-fire
particles and cannot be applied to fire alarms in both large indoor and outdoor open spaces …