This review is focused on video flame and smoke based fire detection algorithms for both
indoor and outdoor environments. It analyzes and discusses them in a taxonomical manner …

The world has seen an increase in the number of wildland fires in recent years due to
various factors. Experts warn that the number of wildland fires will continue to increase in the …

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 …

The recent advances in embedded processing have enabled the vision based systems to
detect fire during surveillance using convolutional neural networks (CNNs). However, such …

Convolutional neural networks (CNNs) have yielded state-of-the-art performance in image
classification and other computer vision tasks. Their application in fire detection systems will …

Fire disasters are man-made disasters, which cause ecological, social, and economic
damage. To minimize these losses, early detection of fire and an autonomous response are …

Wildfires represent a significant natural risk causing economic losses, human death and
environmental damage. In recent years, the world has seen an increase in fire intensity and …

Tactile Internet can combine multiple technologies by enabling intelligence via mobile edge
computing and data transmission over a 5G network. Recently, several convolutional neural …

Fire is one of the most frequent and common emergencies threatening public safety and
social development. Recently, intelligent fire detection technologies represented by …

Vision-based fire detection systems have been significantly improved by deep models;
however, higher numbers of false alarms and a slow inference speed still hinder their …