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Gue-Hwan Nam

2 accepted papers

2020

A Monte Carlo Search-Based Triplet Sampling Method for Learning Disentangled Representation of Impulsive Noise on Steering Gear

ICASSP 2020accepted

The classification task of impact noise on vehicle steering system mainly addresses the issue of modeling the transient and impulsive nature. Though various deep learning models including triplet network have been developed, the existing triplet network based on Euclidean distance metric is limited…

Cited by 0SourceScholar
2020

Data Augmentation Using Empirical Mode Decomposition on Neural Networks to Classify Impact Noise in Vehicle

ICASSP 2020accepted

In a vehicle, impact noise may occur during steering action due to clearance between parts of steering systems. Via structural path the noise is perceived by the drivers' ears and it can be the cause of a repair campaign. It is importatnt to know where the collision occurs to modify the parts causin…

Cited by 0SourceScholar