A fire detection method based on YOLOv5s fused with Swin Transformer is proposed. This is
to address the shortcomings of traditional forest fire detection methods such as poor …

The complexity of fire and smoke in terms of shape, texture, and color presents significant
challenges for accurate fire and smoke detection. To address this, a YOLOv8-based …

Fire accidents have become increasingly frequent and have profound effects on today's
society, leading to injuries, fatalities, and significant economic losses. It is crucial to develop …

Flame detection is of great significance in a fire prevention system. YOLOv4 has poor real-
time performance on flame detection caused by the complex structure and high parameter …

The existing research on fire detection is basically based on a two-stage method, resulting in
slower detection speed, and the positioning accuracy is limited by the first-stage candidate …

For the current mainstream detection methods are difficult to achieve fire detection in
outdoor electric vehicle-charging station, this paper proposes a real-time fire detection …

Fast and highly accurate fire detection algorithms are crucial for production and daily life.
However, detecting fires in the early stages is challenging due to the lack of distinct features …

To address the current difficulties in fire detection algorithms, including inadequate feature
extraction, excessive computational complexity, limited deployment on devices with limited …

Forest fire is a severe natural disaster, which leads to the destruction of forest ecology. At
present, fire detection technology represented by convolutional neural network is widely …

Sensor-based methods and vision-based methods with manual features selection have
been widely used in forest fire detection. However, they have limited detection areas and are …