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Machine learning and landslide studies: recent advances and applications
FS Tehrani, M Calvello, Z Liu, L Zhang, S Lacasse - Natural Hazards, 2022 - Springer
Upon the introduction of machine learning (ML) and its variants, in the form that we know
today, to the landslide community, many studies have been carried out to explore the …
today, to the landslide community, many studies have been carried out to explore the …
[HTML][HTML] Deep learning for geological hazards analysis: Data, models, applications, and opportunities
As natural disasters are induced by geodynamic activities or abnormal changes in the
environment, geological hazards tend to wreak havoc on the environment and human …
environment, geological hazards tend to wreak havoc on the environment and human …
[HTML][HTML] Slope stability prediction using ensemble learning techniques: A case study in Yunyang County, Chongqing, China
W Zhang, H Li, L Han, L Chen, L Wang - Journal of Rock Mechanics and …, 2022 - Elsevier
Slope stability prediction plays a significant role in landslide disaster prevention and
mitigation. This study develops an ensemble learning-based method to predict the slope …
mitigation. This study develops an ensemble learning-based method to predict the slope …
Efficient time-variant reliability analysis of Bazimen landslide in the Three Gorges Reservoir Area using XGBoost and LightGBM algorithms
W Zhang, C Wu, L Tang, X Gu, L Wang - Gondwana Research, 2023 - Elsevier
Abstract The Three Gorges Reservoir Area (TGRA) is one of the most important areas for
landslide prevention and mitigation in China. Rational reliability analysis of reservoir slope …
landslide prevention and mitigation in China. Rational reliability analysis of reservoir slope …
Deep learning methods for time-dependent reliability analysis of reservoir slopes in spatially variable soils
Abstract The Three Gorges Reservoir Area (TGRA) is one of the most important landslide-
prone regions in China, and rational stability evaluation of reservoir slopes in it is of great …
prone regions in China, and rational stability evaluation of reservoir slopes in it is of great …
Landslide detection in the Himalayas using machine learning algorithms and U-Net
SR Meena, LP Soares, CH Grohmann, C Van Westen… - Landslides, 2022 - Springer
Event-based landslide inventories are essential sources to broaden our understanding of
the causal relationship between triggering events and the occurring landslides. Moreover …
the causal relationship between triggering events and the occurring landslides. Moreover …
[HTML][HTML] Effect of attention mechanism in deep learning-based remote sensing image processing: A systematic literature review
S Ghaffarian, J Valente, M Van Der Voort… - Remote Sensing, 2021 - mdpi.com
Machine learning, particularly deep learning (DL), has become a central and state-of-the-art
method for several computer vision applications and remote sensing (RS) image …
method for several computer vision applications and remote sensing (RS) image …
Detection and segmentation of loess landslides via satellite images: A two-phase framework
Landslides are catastrophic natural hazards that often lead to loss of life, property damage,
and economic disruption. Image-based landslide investigations are crucial for determining …
and economic disruption. Image-based landslide investigations are crucial for determining …
[HTML][HTML] Landslide extraction from aerial imagery considering context association characteristics
Accurate extraction of landslide information is crucial for timely disaster emergency
response, yet this process faces significant challenges due to the interference of bare land …
response, yet this process faces significant challenges due to the interference of bare land …