Fires in smart cities can have devastating consequences, causing damage to property, and
endangering the lives of citizens. Traditional fire detection methods have limitations in terms …

Due to the various shapes, textures, and colors of fires, forest fire detection is a challenging
task. The traditional image processing method relies heavily on manmade features, which is …

Deriving individual tree crown (ITC) information from light detection and ranging (LiDAR)
data is of great significance to forest resource assessment and smart management. After …

In the construction of new smart cities, traditional fire-detection systems can be replaced with
vision-based systems to establish fire safety in society using emerging technologies, such as …

Accurate individual tree crown (ITC) segmentation from scanned point clouds is a
fundamental task in forest biomass monitoring and forest ecology management. Light …

Timely detection of forest wildfires is of great significance to the early prevention and control
of large-scale forest fires. Unmanned Aerial Vehicle (UAV) with cameras has the …

Forest fires rank among the costliest and deadliest natural disasters globally. Identifying the
smoke generated by forest fires is pivotal in facilitating the prompt suppression of developing …

Abstract Machine learning-based fire detection/recognition is very popular in forest-
monitoring systems. However, without considering the prior knowledge, eg, equal attention …

Unmanned aerial vehicles (UAVs) are widely used for small target detection of forest fires
due to its low-risk rate, low cost and high ground coverage. However, the detection accuracy …

Forest fires have continually endangered personal safety and social property. To reduce the
occurrences of forest fires, it is essential to detect forest fire smoke accurately and quickly …