Feedback Network With Curriculum Learning for Earthquake Event Classification

In this letter, we propose an earthquake event classification model utilizing a feedback network and curriculum learning (CL). In particular, we propose the CL method with a feature concatenation using gated convolution so that CL can be effectively performed in consideration of the feedback structure. We show that the proposed model is effective through comparison experiments with the existing model using the earthquake dataset for Korean Peninsula and the Stanford earthquake dataset.

Automated summary

The letter proposes an earthquake event classification model utilizing a feedback network and curriculum learning, effectively using feature concatenation and gated convolution for CL. Through comparison experiments with existing models on Korean Peninsula and Stanford earthquake datasets, the effectiveness of the proposed model is demonstrated.