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Transformer and graph convolution-based unsupervised detection of machine anomalous sound under domain shifts
Thanks to the development of deep learning, machine abnormal sound detection (MASD)
based on unsupervised learning has exhibited excellent performance. However, in the task …
based on unsupervised learning has exhibited excellent performance. However, in the task …
Unsupervised anomaly detection and localization of machine audio: A gan-based approach
Automatic detection of machine anomaly remains challenging for machine learning. We
believe the capability of generative adversarial network (GAN) suits the need of machine …
believe the capability of generative adversarial network (GAN) suits the need of machine …
The impact of frequency bands on acoustic anomaly detection of machines using deep learning based model
In this paper, we propose a deep learning based model for Acoustic Anomaly Detection of
Machines, the task for detecting abnormal machines by analysing the machine sound. By …
Machines, the task for detecting abnormal machines by analysing the machine sound. By …
基于域泛化的工业设备无监督异常声音检测算法.
毕忠勤， **欢峰， 张伟娜， 董真 - Science Technology & …, 2024 - search.ebscohost.com
摘要在工业场景中, 因为设备异常现象的罕见性和高度多样化, 以及机器的操作条件或环境噪声
在训练和测试阶段的不同, 会改变训练和测试数据之间的声学特性. 为解决上述问题 …
在训练和测试阶段的不同, 会改变训练和测试数据之间的声学特性. 为解决上述问题 …
ASD-Diff: Unsupervised Anomalous Sound Detection with Masked Diffusion Model
X Fan, W Fang, Y Hu - National Conference on Man-Machine Speech …, 2024 - Springer
Self-supervised methods have achieved state-of-the-art performance in Anomalous Sound
Detection (ASD) task, which exploits manually annotated meta information (ie, section IDs …
Detection (ASD) task, which exploits manually annotated meta information (ie, section IDs …
Anomalous Sound Detection Framework Based on Masking Strategy
X Li, C Zhao, C Gao, W Hu - International Conference on Intelligent …, 2024 - Springer
Abstract Unsupervised Anomalous Sound Detection (ASD) aims to identify abnormal sounds
by learning the features of normal operational sounds and sensing their deviations. Existing …
by learning the features of normal operational sounds and sensing their deviations. Existing …