Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction
- DOI
- 10.3390/s22228790
- Published
- 2022-11-14
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s22228790,
title = {Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction},
author = {Alejandro Casallas and Camila Jiménez-Saenz and Victor Torres and Miguel Quirama-Aguilar and Augusto Lizcano and Ellie Anne Lopez-Barrera and Camilo Ferro and Nathalia Celis and Ricardo Arenas},
year = {2022},
journal = {Sensors},
doi = {10.3390/s22228790},
url = {https://doi.org/10.3390/s22228790}
}RIS
TY - JOUR TI - Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction AU - Alejandro Casallas AU - Camila Jiménez-Saenz AU - Victor Torres AU - Miguel Quirama-Aguilar AU - Augusto Lizcano AU - Ellie Anne Lopez-Barrera AU - Camilo Ferro AU - Nathalia Celis AU - Ricardo Arenas PY - 2022 JO - Sensors DO - 10.3390/s22228790 UR - https://doi.org/10.3390/s22228790 ER -
APA
Casallas, A., Jiménez-Saenz, C., Torres, V., Quirama-Aguilar, M., Lizcano, A., Lopez-Barrera, E. A., Ferro, C., Celis, N., & Arenas, R. (2022). Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction. Sensors. https://doi.org/10.3390/s22228790
Source records
- crossref · retrieved 2026-11-09T17:55:31.706Z