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EdgeFireSmoke++: A novel lightweight algorithm for real-time forest fire detection and visualization using internet of things-human machine interface

  • Published:2023-07 Issue: Volume:221 Page:119747
  • ISSN:0957-4174
  • Container-title:Expert Systems with Applications
  • language:en
  • Short-container-title:Expert Systems with Applications

Author:

Almeida Jefferson S.ORCID,Jagatheesaperumal Senthil KumarORCID,Nogueira Fabrício G.ORCID,de Albuquerque Victor Hugo C.ORCID

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Universidade Federal do Acre

Université de Franche-Comté

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference38 articles.

1. Forest fire detection using classifiers and transfer learning;Agarwal,2021

2. Convolutional neural networks based enhanced forest monitoring system for early fire detection;Chatragadda,2022

3. Chollet, F. (2017). Xception: Deep learning with depthwise separable convolutions. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1251–1258).

4. Lightweight forest fire detection based on deep learning;Fan,2021

5. An appraisal of highest quality studies reporting malignant transformation of oral lichen planus based on a systematic review;González-Moles;Oral Diseases,2021

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