Geoportals in Solving the Problem of Natural Hazards Monitoring
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-54820-8_13
Reference10 articles.
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2. Pelletier, N., Millard, K., Darling, S.: Wildfire likelihood in Canadian treed peatlands based on remote-sensing time-series of surface conditions. Remote Sens. Environ. 296, 113747 (2023). https://doi.org/10.1016/j.rse.2023.113747
3. Thangavel, K., et al.: Autonomous satellite wildfire detection using hyperspectral imagery and neural networks: a case study on Australian wildfire. Remote Sens. (Basel) 15, 720 (2023). https://doi.org/10.3390/rs15030720
4. Yacouby, R., Axman, D.: Probabilistic extension of precision, recall, and F1 score for more thorough evaluation of classification models. In: Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems. Association for Computational Linguistics, Stroudsburg, PA, USA (2020)
5. Deng, M., Tanaka, Y., Li, X.: Experimental study on support vector machine-based early detection for sensor faults and operator-based robust fault tolerant control. Machines 10, 123 (2022). https://doi.org/10.3390/machines10020123
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