سال انتشار:
2021
عنوان انگلیسی مقاله:
A Review on Early Wildfire Detection from Unmanned Aerial Vehicles using Deep Learning-Based Computer Vision Algorithms
ترجمه فارسی عنوان مقاله:
035-S0165168421003467
منبع:
ScienceDirect - Elsevier - Signal Processing Available online 31 August 2021, 108309
نویسنده:
Abdelmalek Bouguettaya
چکیده انگلیسی:
Wildfire is one of the most critical natural disasters that threaten wildlands and forest
resources. Traditional firefighting systems, which are based on ground crew inspection, have several limits and can expose firefightersâĂŹ lives to danger. Thus, remote
sensing technologies have become one of the most demanded strategies to fight against
wildfires, especially UAV-based remote sensing technologies. They have been adopted
to detect forest fires at their early stages, before becoming uncontrollable. Autonomous
wildfire early detection from UAV-based visual data using different deep learning algorithms has attracted significant interest in the last few years. To this end, in this
paper, we focused on wildfires detection at their early stages in forest and wildland areas, using deep learning-based computer vision algorithms to prevent and then reduce
disastrous losses in terms of human lives and forest resources.
Keywords: Computer Vision | Deep Learning | Aerial Images Processing | Wildfire Detection system | Smoke Detection system | Unmanned Aerial Vehicle
قیمت: رایگان
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