Reducing the Parameter Dependency of Phase-Picking Neural Networks with Dice Loss
Training a neural network for picking seismic phase arrivals has been commonly posed as a segmentation problem. It is a highly imbalanced segmentation problem in the sense that the background vastly dominates the foreground because we are trying to pick the optimal single sample point that represent...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Seismological Society of America
2025-01-01
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| Series: | The Seismic Record |
| Online Access: | https://doi.org/10.1785/0320240028 |
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