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Generative self-supervised learning for seismic event classification
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DOI：10.1016/j.engappai.2025.113355.png)
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Abstract
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• Generative self-supervised model for efficient extraction of seismic event features. • Semi-supervised learning approach that minimizes the need for extensive labeled data. • SOM (Self-Organizing Map)-based method to significantly enhance the efficiency of manual data labeling by experts.
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Cited Papers
ShareSaveGraph-Based Feature Weight Optimisation and Classification of Continuous Seismic Sensor Array Recordings.png)
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OAAIShareSaveSTanford EArthquake Dataset (STEAD): A Global Data Set of Seismic Signals for AIIEEE ACCESSOAAI
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OAAIShareSaveShareSaveShareSaveShareSaveIntelligent Recognition of Valid Microseismic Events Based on Self-supervised LearningMEASUREMENT
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