An Efficient U-Net Model for Improved Landslide Detection from Satellite Images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Instrumentation,Geography, Planning and Development
Link
https://link.springer.com/content/pdf/10.1007/s41064-023-00232-4.pdf
Reference70 articles.
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2. Alsabhan W, Alotaiby T, Dudin B (2022) Detecting buildings and nonbuildings from satellite images using U-Net. Comput Intell Neurosci. https://doi.org/10.1155/2022/4831223
3. Amatya P, Kirschbaum D, Stanley T, Tanyas H (2021) Landslide mapping using object-based image analysis and open source tools. Eng Geol 282:106000. https://doi.org/10.1016/j.enggeo.2021.106000
4. Asthana H, Vishwakarma CA, Singh P, Kumar P, Rena V, Mukherjee S (2020) Comparative analysis of pixel and object based classification approach for rapid landslide delineation with the aid of open source tools in Garhwal Himalaya. J Geol Soc India 96(1):65–72. https://doi.org/10.1007/s12594-020-1505-1
5. Ayala C, Sesma R, Aranda C, Galar M (2021) A deep learning approach to an enhanced building footprint and road detection in high-resolution satellite imagery. Remote Sens 13(16):3135. https://doi.org/10.3390/rs13163135
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