Landslide detection based on deep learning and remote sensing imagery: A case study in Linzhi City-Reference-Cited by-同舟云学术

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Landslide detection based on deep learning and remote sensing imagery: A case study in Linzhi City

Published:2024-07 Issue: Volume: Page:
ISSN:2666-5921
Container-title:Natural Hazards Research
language:en
Short-container-title:Natural Hazards Research

Author:

Wang Yutong,Gao Hong,Liu Shuhao,Yang Dayi,Liu Aixuan,Mei Gang^ORCID

Publisher

Elsevier BV

Reference30 articles.

1. Landslide detection from bitemporal satellite imagery using attention-based deep neural networks;Amankwah;Landslides,2022

2. Susceptibility analysis of glacier debris flow based on remote sensing imagery and deep learning: a case study along the g318 linzhi section;Chen;Sensors,2023

3. A global-local self-adaptive network for drone-view object detection;Deng;IEEE Trans. Image Process.,2021

4. Co-seismic landslide hazard assessment of the 2017 ms 6.9 milin earthquake, tibet, China, combining the logistic regression-information value and newmark displacement models;Du;Bull. Eng. Geol. Environ.,2022

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