A comprehensive comparison study of traditional classifiers and deep neural networks for forest fire detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Link
https://link.springer.com/content/pdf/10.1007/s10586-023-04003-z.pdf
Reference59 articles.
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2. Lalitha, K., Veerapandu, G.: Forest fire detection using satellite images. Smart Innov. Syst. Technol. 290, 277–284 (2023). https://doi.org/10.1007/978-981-19-0108-9_29/COVER
3. Verma, N., Singh, D.: Analysis of cost-effective sensors: data Fusion approach used for forest fire application. Mater. Today Proc. 24, 2283–2289 (2020). https://doi.org/10.1016/J.MATPR.2020.03.756
4. González, T.M., González-Trujillo, J.D., Muñoz, A., Armenteras, D.: Differential effects of fire on the occupancy of small mammals in neotropical savanna-gallery forests. Perspect. Ecol. Conserv. 19, 179–188 (2021). https://doi.org/10.1016/j.pecon.2021.03.005
5. Chowdary, V., Gupta, M.K.: Automatic forest fire detection and monitoring techniques: a survey. Adv. Intell. Syst. Comput. 624, 1111–1117 (2018). https://doi.org/10.1007/978-981-10-5903-2_116/COVER
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