38 citations as recorded by crossref.

1. Application of artificial intelligence technology in the study of anthropogenic earthquakes: a review J. Li et al. 10.1007/s10462-025-11157-2
2. Rockfall alarm system for railway monitoring: Integrating seismic detection, localization, and characterization T. Rebert et al. 10.1190/geo2023-0058.1
3. Coordinated analysis of county geological environment carrying capacity and sustainable development under remote sensing interpretation combined with integrated model X. Wang et al. 10.1016/j.ecoenv.2023.114956
4. Assessment of environmental geological disaster susceptibility under a multimodel comparison to aid in the sustainable development of the regional economy C. Wang et al. 10.1007/s11356-022-22649-x
5. Cluster Analysis of Slope Hazard Seismic Recordings Based Upon Unsupervised Deep Embedded Clustering C. Wang et al. 10.1785/0220230011
6. Earthquake signal detection using a multiscale feature fusion network with hybrid attention mechanism Y. Cui et al. 10.1093/gji/ggae423
7. Analysis of Thermally Induced Strain Effects on a Jointed Rock Mass through Microseismic Monitoring at the Acuto Field Laboratory (Italy) G. Grechi et al. 10.3390/app13042489
8. Rock avalanche-induced air blasts: Implications for landslide risk assessments Y. Zhuang et al. 10.1016/j.geomorph.2024.109111
9. Event recognition in marine seismological data using Random Forest machine learning classifier P. Domel et al. 10.1093/gji/ggad244
10. Seismometer Records of Ground Tilt Induced by Debris Flows M. Wenner et al. 10.1785/0120210271
11. Graph-Based Feature Weight Optimisation and Classification of Continuous Seismic Sensor Array Recordings J. Li et al. 10.3390/s23010243
12. A real scale application of a novel set of spatial and similarity features for detection and classification of natural seismic sources from distributed acoustic sensing data C. Huynh et al. 10.1093/gji/ggae382
13. Microseismic Event Classification With Time-, Frequency-, and Wavelet-Domain Convolutional Neural Networks J. Jiang et al. 10.1109/TGRS.2023.3262412
14. RockNet: Rockfall and Earthquake Detection and Association via Multitask Learning and Transfer Learning W. Liao et al. 10.1109/TGRS.2023.3284008
15. Multi-temporal InSAR-based landslide dynamic susceptibility mapping of Fengjie County, Three Gorges Reservoir Area, China F. Tian et al. 10.1016/j.jrmge.2025.01.012
16. Automated classification of seismic signals recorded on the Åknes rock slope, Western Norway, using a convolutional neural network N. Langet & F. Silverberg 10.5194/esurf-11-89-2023
17. Ensemble Learning Improves the Efficiency of Microseismic Signal Classification in Landslide Seismic Monitoring B. Xin et al. 10.3390/s24154892
18. Integrating multi-source monitoring data and deep convolutional autoencoder technology for slope failure pattern recognition N. Han et al. 10.3389/feart.2025.1531857
19. Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment J. Hirschberg et al. 10.5194/nhess-21-2773-2021
20. A clustering-classification approach in categorizing vulnerability of roads and bridges using public assistance big data A. Bhattacharyya et al. 10.1016/j.ijdrr.2022.103448
21. Seismogenic landslides volume and runout estimation with machine learning C. Hibert et al. 10.1007/s10346-025-02496-w
22. Machine Learning and Imbalanced Learning Approaches in Condition-Based Monitoring and Predictive Maintenance: A Systematic Literature Review A. Mutemi & F. Bacao 10.2139/ssrn.3980484
23. Near-real-time detection of co-seismic ionospheric disturbances using machine learning Q. Brissaud & E. Astafyeva 10.1093/gji/ggac167
24. Discrimination between icequakes and earthquakes in southern Alaska: an exploration of waveform features using Random Forest algorithm A. Kharita et al. 10.1093/gji/ggae106
25. Rapid resilience assessment framework for mountain tunnels subjected to near-fault seismic ground motions S. Meng et al. 10.1016/j.soildyn.2024.108746
26. EQTypeNet: deep learning tri-branch earthquake automatic classification model and its application in China T. Lu et al. 10.1093/gji/ggaf263
27. How water, temperature, and seismicity control the preconditioning of massive rock slope failure (Hochvogel) J. Leinauer et al. 10.5194/esurf-12-1027-2024
28. Real-Time Classification of Anthropogenic Seismic Sources from Distributed Acoustic Sensing Data: Application for Pipeline Monitoring C. Huynh et al. 10.1785/0220220078
29. Domain Knowledge Informed Multitask Learning for Landslide-Induced Seismic Classification J. Li et al. 10.1109/LGRS.2023.3279068
30. Machine learning prediction of the mass and the velocity of controlled single-block rockfalls from the seismic waves they generate C. Hibert et al. 10.5194/esurf-12-641-2024
31. Cyborg insect repeatable self-righting locomotion assistance using bio-inspired 3D printed artificial limb M. Montagut Marques et al. 10.1038/s44182-024-00009-w
32. Debris flows at Illgraben, Switzerland – From seismic wiggles to machine learning F. Walter et al. 10.1002/geot.202200039
33. Machine learning prediction of groundwater heights from passive seismic wavefield A. Abi Nader et al. 10.1093/gji/ggad160
34. A Clustering-Classification Approach in Categorizing Vulnerability of Roads and Bridges Using Public Assistance Big Data A. Bhattacharyya et al. 10.2139/ssrn.4165442
35. Seismic Advances in Process Geomorphology K. Cook & M. Dietze 10.1146/annurev-earth-032320-085133
36. Intelligent detection of underground openings and surrounding disturbed zones W. Meng et al. 10.1016/j.tust.2024.106122
37. Characterizing the evolution of mass flow properties and dynamics through analysis of seismic signals: insights from the 18 March 2007 Mt. Ruapehu lake-breakout lahar B. Walsh et al. 10.5194/nhess-23-1029-2023
38. Machine Learning Improves Debris Flow Warning M. Chmiel et al. 10.1029/2020GL090874