Automatic recognition of landslides based on YOLOv7 and attention mechanism
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11629-024-8669-x.pdf
Reference43 articles.
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2. Alexandra G, Erin L, Ola F, et al. (2023). Globally vs. locally trained machine learning models for landslide detection: A case study of a glacial landscape. Remote Sens 15(4):895. 15.895.10.3390/rs15040895
3. Bell R, Monique F, Joachim G, et al. (2020) Major geomorphic events and natural hazards during monsoonal precipitation 2018 in the Kali Gandaki Valley. Nepal Himalaya. Geomorphology 372: 107451. https://doi.org/10.1016/j.geomorph.2020.107451
4. Bellotti F, Bianchi M, Colombo D, et al. (2014) Advanced InSAR techniques to support landslide monitoring. Mathematics of planet earth, Springer. pp 287–290. https://doi.org/10.1007/978-3-642-32408-6_64
5. Cui P, Zhu YY, Han YS, et al. (2009) The 12 May Wenchuan earthquake-induced landslide lakes: distribution and preliminary risk evaluation. Landslides 6: 209–223. https://doi.org/10.1007/s10346-009-0160-9
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