Due to the harm forest fires cause to the environment and the economy as they occur more
frequently around the world, early fire prediction and detection are necessary. To anticipate …

Fire is indeed one of the major contributing factors to fatalities, property damage, and
economic disruption. A large number of fire incidents across the world cause devastation …

As a new fire detection technology, image fire detection has recently played a crucial role in
reducing fire losses by alarming users early through early fire detection. Image fire detection …

For the detection of small targets, fire-like and smoke-like targets in forest fire images, as
well as fire detection under different natural lights, an improved Fire-YOLO deep learning …

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 …

This work presents a real-time video-based fire and smoke detection using YOLOv2
Convolutional Neural Network (CNN) in antifire surveillance systems. YOLOv2 is designed …

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

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 …