Deep Learning Approaches for Wildland Fires Remote Sensing: Classification, Detection, and Segmentation

R Ghali, MA Akhloufi - Remote Sensing, 2023 - mdpi.com
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 …

A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management

SPH Boroujeni, A Razi, S Khoshdel, F Afghah… - Information …, 2024 - Elsevier
Wildfires have emerged as one of the most destructive natural disasters worldwide, causing
catastrophic losses. These losses have underscored the urgent need to improve public …

Improved real-time fire warning system based on advanced technologies for visually impaired people

AB Abdusalomov, M Mukhiddinov, A Kutlimuratov… - Sensors, 2022 - mdpi.com
Early fire detection and notification techniques provide fire prevention and safety information
to blind and visually impaired (BVI) people within a short period of time in emergency …

FCDM: An improved forest fire classification and detection model based on YOLOv5

Q Xue, H Lin, F Wang - Forests, 2022 - mdpi.com
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 …

Advancements in forest fire prevention: A comprehensive survey

F Carta, C Zidda, M Putzu, D Loru, M Anedda, D Giusto - Sensors, 2023 - mdpi.com
Nowadays, the challenges related to technological and environmental development are
becoming increasingly complex. Among the environmentally significant issues, wildfires …

Monitoring and cordoning wildfires with an autonomous swarm of unmanned aerial vehicles

F Saffre, H Hildmann, H Karvonen, T Lind - Drones, 2022 - mdpi.com
Unmanned aerial vehicles, or drones, are already an integral part of the equipment used by
firefighters to monitor wildfires. They are, however, still typically used only as remotely …

Suburban Forest Fire Risk Assessment and Forest Surveillance Using 360-Degree Cameras and a Multiscale Deformable Transformer

P Barmpoutis, A Kastridis, T Stathaki, J Yuan, M Shi… - Remote Sensing, 2023 - mdpi.com
In the current context of climate change and demographic expansion, one of the phenomena
that humanity faces are the suburban wildfires. To prevent the occurrence of suburban forest …

Litchi detection in a complex natural environment using the YOLOv5-litchi model

J Xie, J Peng, J Wang, B Chen, T Jing, D Sun, P Gao… - Agronomy, 2022 - mdpi.com
Detecting litchis in a complex natural environment is important for yield estimation and
provides reliable support to litchi-picking robots. This paper proposes an improved litchi …

An improved forest fire and smoke detection model based on yolov5

J Li, R Xu, Y Liu - Forests, 2023 - mdpi.com
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 …

[HTML][HTML] Ten deep learning techniques to address small data problems with remote sensing

A Safonova, G Ghazaryan, S Stiller… - International Journal of …, 2023 - Elsevier
Researchers and engineers have increasingly used Deep Learning (DL) for a variety of
Remote Sensing (RS) tasks. However, data from local observations or via ground truth is …