TY - GEN
T1 - From Global to Local
T2 - 7th IEEE International Conference on BioInspired Processing, BIP 2025
AU - Gamboa-Chacón, Sebastián
AU - Salas, Nahomy Campos
AU - Chaves, Esteban J.
AU - Meneses, Esteban
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Seismology has advanced significantly with the integration of artificial intelligence. In seismic phase detection, a key step in constructing earthquake catalogs, modern tools can now identify picks with high accuracy and reliability. EQTransformer is a deep learning model originally trained on STEAD, a global seismic dataset. However, its performance may be limited in regions underrepresented in the training data. This study explores the fine-tuning of EQTransformer using Costa Rican seismic waveforms, with an extended dataset of 7,426 event picks detected using manual methods, recorded nationwide in February 2025. The model was adapted by freezing the final layers and retraining the previous ones. Evaluation in the Tilarán region demonstrates improved detection of local seismic phases, leading to more reliable catalogs and underscoring the potential of transfer learning for regional earthquake monitoring.
AB - Seismology has advanced significantly with the integration of artificial intelligence. In seismic phase detection, a key step in constructing earthquake catalogs, modern tools can now identify picks with high accuracy and reliability. EQTransformer is a deep learning model originally trained on STEAD, a global seismic dataset. However, its performance may be limited in regions underrepresented in the training data. This study explores the fine-tuning of EQTransformer using Costa Rican seismic waveforms, with an extended dataset of 7,426 event picks detected using manual methods, recorded nationwide in February 2025. The model was adapted by freezing the final layers and retraining the previous ones. Evaluation in the Tilarán region demonstrates improved detection of local seismic phases, leading to more reliable catalogs and underscoring the potential of transfer learning for regional earthquake monitoring.
KW - Deep Learning
KW - EQTransformer
KW - Fine-Tuning
KW - Seismic Phase Detection
KW - Seismology
KW - Transfer Learning
UR - https://www.scopus.com/pages/publications/105038705138
U2 - 10.1109/BIP68491.2025.11489131
DO - 10.1109/BIP68491.2025.11489131
M3 - Contribución a la conferencia
AN - SCOPUS:105038705138
T3 - 2025 IEEE 7th International Conference on BioInspired Processing, BIP 2025
BT - 2025 IEEE 7th International Conference on BioInspired Processing, BIP 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 December 2025 through 5 December 2025
ER -