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Feedback Network With Curriculum Learning for Earthquake Event Classification
- Authors
- Min, Jeongki; Ku, Bonwha; Ko, Hanseok
- Issue Date
- 2022
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Earthquakes; Feature extraction; Convolution; Logic gates; Hidden Markov models; Kernel; Task analysis; Convolutional neural network (CNN); curriculum learning (CL); earthquake event classification; feature fusion; feedback
- Citation
- IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, v.19
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
- Volume
- 19
- ISSN
- 1545-598X
- Abstract
- 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.
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Related Researcher
- Ko, Han seok
- College of Engineering (School of Electrical Engineering)