Early stage smoke detection using image and video analysis is an important area of
research due to its enormous applications in mitigating fire hazards and ensuring …

The Transformer network was originally proposed for natural language processing. Due to
its powerful representation ability for long-range dependency, it has been extended for …

Existing vision-based smoke recognition methods still face the issues of low detection rates
and high false alarm rates in complex scenes. One reason is that they label light smoke and …

Forest fires pose a significant threat to both the economy and ecology, causing extensive
damage. Smoke serves as a crucial indicator of forest fires, often appearing before the …

Smoke has semi-transparency property leading to highly complicated mixture of background
and smoke. Sparse or small smoke is visually inconspicuous, and its boundary is often …

In this paper, the problem of dynamical deployment of unmanned aerial vehicles (UAVs)
equipped with visible light communication (VLC) capabilities for optimizing the energy …

To obtain real-time performance on computation limited devices, we propose a lightweight
network for smoke segmentation. To enhance the ability of feature encoding, we first …

Smoke has large variances of visual appearances that are very adverse to visual
segmentation. Furthermore, its semi-transparency often produces highly complicated …

It is very challenging to accurately segment smoke images because smoke has some
adverse properties, such as semi-transparency and blurry boundary. Aiming at solving these …

Smoke detection is a key process for fire warning systems. However, the existing smoke
detection methods are insufficient to extract precise smoke features due to the smoke's …