The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
A review on early wildfire detection from unmanned aerial vehicles using deep learning-based computer vision algorithms
Abstract
Abstract 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 firefighters’ 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.
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Cites
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Wildfire and Smoke Detection Using Staged YOLO Model and Ensemble CNN
Bahhar, C., Ksibi, A., Ayadi, M., Jamjoom, M. M., Ullah, Z., Soufiene, B. O., & Sakli, H. (2023) · Electronics · doi:10.3390/electronics12010228 · Cited by 99
An efficient deepfake video detection using robust deep learning
Qadir, A., Mahum, R., El-Meligy, M. A., Ragab, A. E., AlSalman, A., & Awais, M. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e25757 · Cited by 78
Metadata
- Authors
- Bouguettaya, A., Zarzour, H., Taberkit, A. M., & Kechida, A.
- Venue
- Signal Processing
- Publisher
- Elsevier BV
- Published
- 2022-01
- Volume
- 190
- Pages
- 108309
- ISSN
- 0165-1684 (ISSN-L)
- OpenAlex
- W3196908521
- Cited by
- 287
- References
- 15
- FWCI
- 30.76
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bouguettaya, A., Zarzour, H., Taberkit, A. M., & Kechida, A. (2022). A review on early wildfire detection from unmanned aerial vehicles using deep learning-based computer vision algorithms. Signal Processing. https://doi.org/10.1016/j.sigpro.2021.108309
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
