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Unsupervised Acoustic Anomaly Detection Systems Based on Gaussian Mixture Density Neural Network

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dc.contributor.authorLiu, Zhaoyi
dc.contributor.authorTang, Haoyu
dc.contributor.authorMichiels, Sam
dc.contributor.authorJoosen, Wouter
dc.contributor.authorHughes, Danny
dc.contributor.imecauthorJoosen, Wouter
dc.date.accessioned2023-05-31T09:47:29Z
dc.date.available2023-02-23T03:25:34Z
dc.date.available2023-05-31T09:47:29Z
dc.date.issued2022
dc.description.wosFundingTextThis research is partially funded by the Research Fund KU Leuven, and by imec and Flanders Innovation Entrepreneurship (VLAIO) in the context of the WiPeR project.
dc.identifier.eisbn978-90-827970-9-1
dc.identifier.issn2076-1465
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/41128
dc.publisherIEEE
dc.source.beginpage259
dc.source.conference30th European Signal Processing Conference (EUSIPCO)
dc.source.conferencedateAUG 29-SEP 02, 2022
dc.source.conferencelocationBelgrade
dc.source.endpage263
dc.source.journalna
dc.source.numberofpages5
dc.title

Unsupervised Acoustic Anomaly Detection Systems Based on Gaussian Mixture Density Neural Network

dc.typeProceedings paper
dspace.entity.typePublication
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