Anomalous sound detection - Open Access .click

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Anomalous sound detection with timbre separation

2022
MORIKUNI SHU +4 more
openaire +1 more source

Anomalous sound detection apparatus, degree-of-anomaly calculation apparatus, anomalous sound generation apparatus, anomalous sound detection training apparatus, anomalous signal detection apparatus, anomalous signal detection training apparatus, and methods and programs therefor

2023
KOIZUMI YUMA, SAITO SHOICHIRO, UEMATSU HISASHI +2 more
openaire +1 more source

MDAM: Multi-Dimensional Attention Module for Anomalous Sound Detection

2023
Shengbing Chen, Junjie Wang, Jiajun Wang, Zhiqi Xu +3 more
openaire +2 more sources

Anomalous Sound Detection Using a Binary Classification Model and Class Centroids

2021
Kazuya Takeda, Tomoki Toda
exaly

Anomalous Sound Detection by Feature-Level Anomaly Simulation

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Vitjan Zavrtanik +3 more
openaire +1 more source

Online detection method for variable load conditions and anomalous sound of hydro turbines using correlation analysis and PCA-adaptive-K-means

Measurement: Journal of the International Measurement Confederation
He Wen, Lin Haijun, Xiong Xu
exaly

Lightweight Anomalous Detection of Hydro Turbine Operation Sound Using Fusion Network Enhanced by Load Information

IEEE Transactions on Instrumentation and Measurement
He Wen, Lin Haijun, Zhongwen Li
exaly

Anomalous Sound Detection Framework Based on Masking Strategy

Xiang Li, Caidan Zhao, Chenxing Gao, Wenxin Hu +3 more
openaire +1 more source

Spectro Temporal Fusion with CLSTM-Autoencoder based approach for Anomalous Sound Detection

Neural Processing Letters
Chandrakala S
exaly

Method and system for detecting anomalous sound

WICHERN GORDON +3 more
openaire +2 more sources

fos: computer and information sciences
sound cs.sd
audio and speech processing eess.as

computer science - sound
deep learning
machine learning cs.lg

computer science - machine learning
anomaly detection
self-supervised learning