Feedback Network with Curriculum Learning for Earthquake Event Classification

Jeongki Min, Bonwha Ku, Hanseok Ko

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
JournalIEEE Geoscience and Remote Sensing Letters
Publication statusPublished - 2022


  • Convolutional neural network (CNN)
  • curriculum learning (CL)
  • earthquake event classification
  • feature fusion
  • feedback

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering


Dive into the research topics of 'Feedback Network with Curriculum Learning for Earthquake Event Classification'. Together they form a unique fingerprint.

Cite this