Domain knowledge informed multitask learning for landslide induced seismic classification

Automatic seismic signal classification methods are extensively investigated to reduce or replace manual interpretation, with great potential in previous research. Discriminative seismic wave propagation physical characteristics, such as velocities and accelerations, are rarely considered for classi...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters 2023-01, Vol.20, p.1-1
Hauptverfasser:	Li, Jiangfeng, Ye, Minxiang, Stankovic, Lina, Stankovic, Vladimir, Pytharouli, Stella
Format:	Artikel
Sprache:	eng
Schlagworte:	Anthropogenic factors Artificial neural networks Classification Earthquakes Feature extraction Feature maps landslide-induced seismic classification Landslides Learning Machine learning Mathematical models Monitoring multitask learning Neural networks P waves P-wave velocity Physical characteristics Physical properties Recording Rock falls Rockfall Seismic activity Seismic propagation Seismic velocities Seismic wave equation Seismic wave propagation Seismic wave velocities Seismic waves Signal classification Signal representation Solid modeling Wave equations Wave propagation Wave velocity
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