Strategy of oversampling geotechnical parameters through geostatistical, SMOTE, and CTGAN methods for assessing susceptibility of landslide

SMOTE: Synthetic Minority Over-sampling Technique

Nitesh V. Chawla, Kevin W. Bowyer, Lawrence Hall et al. · Journal of Artificial Intelligence Research · 2002 · 31.2K citations · Full text

Computing, Computer Science, Data Science +12

ADASYN: Adaptive synthetic sampling approach for imbalanced learning

Haibo He, Yang Bai, Edwardo A. Garcia et al. · 2008 · 4.4K citations

Computing, Computer Science, Data Mining +16

Finding the right pixel size

Tomislav Hengl · Computers & Geosciences · 2006 · 830 citations

Computing, Computer Engineering, Computer Science +4

Application of deep learning algorithms in geotechnical engineering: a short critical review

Wengang Zhang, Hongrui Li, Yongqin Li et al. · Artificial Intelligence Review · 2021 · 509 citations

Engineering, Civil Engineering, Geological Engineering +14

Predictive Performances of Ensemble Machine Learning Algorithms in Landslide Susceptibility Mapping Using Random Forest, Extreme Gradient Boosting (XGBoost) and Natural Gradient Boosting (NGBoost)

Taşkın Kavzoğlu, Alihan Teke · Arabian Journal for Science and Engineering · 2022 · 343 citations

Computing, Computer Science, Earth Sciences +17