Forest fire and smoke detection using deep learning-based learning without forgetting

Sathishkumar, V E; Cho, Jaehyuk; Subramanian, Malliga; Naren, Obuli Sai

doi:10.1186/s42408-022-00165-0

articleFire EcologyFeb 17, 2023GOLD OA

Forest fire and smoke detection using deep learning-based learning without forgetting

VEV E Sathishkumar JCJaehyuk Cho MSMalliga Subramanian OSObuli Sai Naren

Jeonbuk National University

Indexed incrossrefdoaj

Abstract

Abstract Background Forests are an essential natural resource to humankind, providing a myriad of direct and indirect benefits. Natural disasters like forest fires have a major impact on global warming and the continued existence of life on Earth. Automatic identification of forest fires is thus an important field to research in order to minimize disasters. Early fire detection can also help decision-makers plan mitigation methods and extinguishing tactics. This research looks at fire/smoke detection from images using AI-based computer vision techniques. Convolutional Neural Networks (CNN) are a type of Artificial Intelligence (AI) approach that have been shown to outperform state-of-the-art methods in image…

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231

total citations

FWCI: 44.32
Percentile: 100%
References: 47

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Authors

4

Topics & keywords

Topics

Keywords

Transfer of learning
Computer science
Convolutional neural network
Forgetting
Artificial intelligence
Deep learning
Task (project management)
Machine learning

UN Sustainable Development Goals

Climate action

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