In the context of large-scale fire areas and complex forest environments, the task of
identifying the subtle features and aspects of fire can pose a significant challenge for the …

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 …

Forest fires are destructive and rapidly spreading, causing great harm to forest ecosystems
and humans. Deep learning techniques can adaptively learn and extract features of forest …

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 …

Forest fires present a significant challenge to ecosystems, particularly due to factors like tree
cover that complicate fire detection tasks. While fire detection technologies, like YOLO, are …

The frequent occurrence of forest fires causes irreparable damage to the environment and
the economy. Therefore, the accurate detection of forest fires is particularly important. Due to …

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 …

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

Forest fires result in severe disaster, causing significant ecological damage and substantial
economic losses. Flames and smoke represent the predominant characteristics of forest …

Forest resources safety is of paramount importance for natural and public security. Forest fire
detection methods have been attracted much attention recently, but the performance in …