Classification and detection of natural disasters using machine learning and deep learning techniques: A review-Reference-Cited by-同舟云学术

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Classification and detection of natural disasters using machine learning and deep learning techniques: A review

Published:2023-12-28 Issue: Volume: Page:
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Abraham Kibitok,Abdelwahab Moataz,Abo-Zahhad Mohammed

Funder

Science, Technology, and Innovation Funding Authority

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

https://link.springer.com/content/pdf/10.1007/s12145-023-01205-2.pdf

Reference132 articles.

1. Aamir M, Ali T, Irfan M et al (2021) Natural Disasters intensity analysis and classification based on multispectral images using multi-layered deep convolutional neural network. Sensors 21:2648. https://doi.org/10.3390/s21082648

2. Abraham K, Abdelwahab M, Abo-Zahhad M (2022a) Image Classification of Natural Disasters Using Different Deep Learning Models. In: 2022 10th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC). IEEE, pp 191–196

3. Abraham S, Thomas VRJ, Jose S (2022b) B Comparative Analysis of Various Machine Learning Techniques for Flood Prediction. In: 2022 International Conference on Innovative Trends in Information Technology (ICITIIT). IEEE, pp 1–5

4. Akiba T, Sano S, Yanase T et al (2019) Optuna: A Next-generation Hyperparameter Optimization Framework. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

5. Alam F, Alam T, Hasan MA et al (2023) MEDIC: a multi-task learning dataset for Disaster image classification. Neural Comput Appl 35:2609–2632. https://doi.org/10.1007/s00521-022-07717-0

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