1 citations · 1 across the 5 of their papers we have counts for
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Transformer-based Autoencoder with ID Constraint for Unsupervised Anomalous Sound Detection
Jian Guan, Youde Liu, Qiuqiang Kong +4
Unsupervised anomalous sound detection (ASD) aims to detect unknown anomalous sounds of devices when only normal sound data is available. The autoencoder (AE) and self-supervised l…
Anomalous Sound Detection Using Self-Attention-Based Frequency Pattern Analysis of Machine Sounds
Hejing Zhang, Jian Guan, Qiaoxi Zhu +2
Different machines can exhibit diverse frequency patterns in their emitted sound. This feature has been recently explored in anomaly sound detection and reached state-of-the-art pe…
Anomalous Sound Detection using Audio Representation with Machine ID based Contrastive Learning Pretraining
Jian Guan, Feiyang Xiao, Youde Liu +2
Existing contrastive learning methods for anomalous sound detection refine the audio representation of each audio sample by using the contrast between the samples' augmentations (e…
Anomalous Sound Detection using Spectral-Temporal Information Fusion
Youde Liu, Jian Guan, Qiaoxi Zhu +1
Unsupervised anomalous sound detection aims to detect unknown abnormal sounds of machines from normal sounds. However, the state-of-the-art approaches are not always stable and per…