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- W2980591981 abstract "Earthquakes and tropical cyclones cause the suffering of millions of people around the world every year. The resulting landslides exacerbate the effects of these disasters. Landslide detection is, therefore, a critical task for the protection of human life and livelihood in mountainous areas. To tackle this problem, we propose a combination of satellite technology and Deep Neural Networks (DNNs). We evaluate the performance of multiple DNN-based methods for landslide detection on actual satellite images of landslide damage. Our analysis demonstrates the potential for a meaningful social impact in terms of disasters and rescue." @default.
- W2980591981 created "2019-10-25" @default.
- W2980591981 creator A5065015874 @default.
- W2980591981 date "2019-10-15" @default.
- W2980591981 modified "2023-09-27" @default.
- W2980591981 title "Large-Scale Landslides Detection from Satellite Images with Incomplete Labels" @default.
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- W2980591981 doi "https://doi.org/10.48550/arxiv.1910.07129" @default.
- W2980591981 hasPublicationYear "2019" @default.
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