most citedSound-based drone fault classification using multitask learning

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2024

3D Room Geometry Inference from Multichannel Room Impulse Response using Deep Neural Network

Inmo Yeon, Jung-Woo Choi

Room geometry inference (RGI) aims at estimating room shapes from measured room impulse responses (RIRs) and has received lots of attention for its importance in environment-aware…

cs.SD2023

Noisy-ArcMix: Additive Noisy Angular Margin Loss Combined With Mixup Anomalous Sound Detection

Soonhyeon Choi, Jung-Woo Choi

Unsupervised anomalous sound detection (ASD) aims to identify anomalous sounds by learning the features of normal operational sounds and sensing their deviations. Recent approaches…

eess.AS2023

Divided spectro-temporal attention for sound event localization and detection in real scenes for DCASE2023 challenge

Yusun Shul, Byeong-Yun Ko, Jung-Woo Choi

Localizing sounds and detecting events in different room environments is a difficult task, mainly due to the wide range of reflections and reverberations. When training neural netw…

cs.SD20232 cited

Sound-based drone fault classification using multitask learning

Wonjun Yi, Jung-Woo Choi, Jae-Woo Lee

The drone has been used for various purposes, including military applications, aerial photography, and pesticide spraying. However, the drone is vulnerable to external disturbances…

cs.SD2023

On-site Noise Exposure technique for noise-robust machine fault classification

Wonjun Yi, Jung-Woo Choi

In-situ classification of faulty sounds is an important issue in machine health monitoring and diagnosis. However, in a noisy environment such as a factory, machine sound is always…