Code for "Classification of seismic events in the mainland of China based on spectrograms and model interpretability"
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2026
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| _version_ | 1866902192637607936 |
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| author | Chen, Yongjie Xiao, Zhuo |
| author_facet | Chen, Yongjie Xiao, Zhuo |
| contents | <h2>Version 3.0</h2> <p>This repository contains the complete code implementation for "Classification of seismic events in the mainland of China based on spectrograms and model interpretability".</p> <p>The upload includes two main components:</p> <h3>1. ResWaveQuake_Classification.zip</h3> <p>Implementation of seismic event classification using ResWaveQuake encoder architecture. The framework performs <strong>3-class classification</strong> on seismic waveform data using spectrogram-based analysis with PyTorch Lightning.</p> <p><strong>Key features:</strong></p> <ul> <li>ResWaveQuake encoder for feature extraction</li> <li><strong>3-class classification</strong>: Natural earthquake events (EQ), explosion events (EP), and collapse events (CL)</li> <li>Event-level prediction with majority voting across components</li> <li>Automatic class balancing and comprehensive evaluation</li> <li>Support for multiple seismic data formats (.mseed, .seed, .SAC, etc.)</li> <li>Resume training capability from checkpoints</li> </ul> <h3>2. Code for Interpretability Analysis.zip (Version 3.0)</h3> <p>Comprehensive interpretability analysis tools for understanding model decisions and feature importance in seismic event classification.</p> <p><strong>Components include:</strong></p> <ul> <li>Cumulative heatmap analysis experiments</li> <li>Occlusion-based interpretability tests</li> <li>Single-event interpretation analysis</li> </ul> <p><strong>Version 3.0 Updates:</strong></p> <ul> <li>Corrected manuscript title</li> <li>Updated color schemes in epicentral distance-based cumulative interpretability figures to improve accessibility for color vision deficiency</li> </ul> <p>Both packages include detailed README files with installation instructions and usage guidelines.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18603481 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Code for "Classification of seismic events in the mainland of China based on spectrograms and model interpretability" Chen, Yongjie Xiao, Zhuo Deep Learning/classification Seismic Classification Interpretability Analysis <h2>Version 3.0</h2> <p>This repository contains the complete code implementation for "Classification of seismic events in the mainland of China based on spectrograms and model interpretability".</p> <p>The upload includes two main components:</p> <h3>1. ResWaveQuake_Classification.zip</h3> <p>Implementation of seismic event classification using ResWaveQuake encoder architecture. The framework performs <strong>3-class classification</strong> on seismic waveform data using spectrogram-based analysis with PyTorch Lightning.</p> <p><strong>Key features:</strong></p> <ul> <li>ResWaveQuake encoder for feature extraction</li> <li><strong>3-class classification</strong>: Natural earthquake events (EQ), explosion events (EP), and collapse events (CL)</li> <li>Event-level prediction with majority voting across components</li> <li>Automatic class balancing and comprehensive evaluation</li> <li>Support for multiple seismic data formats (.mseed, .seed, .SAC, etc.)</li> <li>Resume training capability from checkpoints</li> </ul> <h3>2. Code for Interpretability Analysis.zip (Version 3.0)</h3> <p>Comprehensive interpretability analysis tools for understanding model decisions and feature importance in seismic event classification.</p> <p><strong>Components include:</strong></p> <ul> <li>Cumulative heatmap analysis experiments</li> <li>Occlusion-based interpretability tests</li> <li>Single-event interpretation analysis</li> </ul> <p><strong>Version 3.0 Updates:</strong></p> <ul> <li>Corrected manuscript title</li> <li>Updated color schemes in epicentral distance-based cumulative interpretability figures to improve accessibility for color vision deficiency</li> </ul> <p>Both packages include detailed README files with installation instructions and usage guidelines.</p> |
| title | Code for "Classification of seismic events in the mainland of China based on spectrograms and model interpretability" |
| topic | Deep Learning/classification Seismic Classification Interpretability Analysis |
| url | https://doi.org/10.5281/zenodo.18603481 |