Fire-detection technology is of great importance for successful fire-prevention measures.
Image-based fire detection is one effective method. At present, object-detection algorithms …

This work suggests an enhanced natural environment animal detection algorithm based on
YOLOv5s to address the issues of low detection accuracy and sluggish detection speed …

The quantitative simulation of forest fire spread is of great significance for designing rapid
risk management approaches and implementing effective fire fighting strategies. A cellular …

To tackle the problem of missed detections in long-range detection scenarios caused by the
small size of forest fire targets, initiatives have been undertaken to enhance the feature …

Real-time and accurate detection of flame and smoke is an important prerequisite to reduce
the loss caused by fire. There are exists some problems in traditional detection algorithms of …

With the influence of climate change and human activities, the frequency and scale of forest
fires have been increasing continuously, posing a significant threat to the environment and …

Owing to the problems of missed detection, false detection, and low accuracy of the current
fire detection algorithm, a segmentation detection algorithm, YOLO-SF, is proposed. This …

Given the limited computing capabilities of UAV terminal equipment, there is a challenge in
balancing the accuracy and computational cost when deploying the target detection model …

Nowadays, deep learning algorithms are widely used in forest fire monitoring systems. In
high-altitude mon-itoring, the sizes of flames are too small, and they are potentially heavily …

Ship fires are one of the main factors that endanger the safety of ships; because the ship is
far away from land, the fire can be difficult to extinguish and could often cause huge losses …