{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T17:00:35Z","timestamp":1785603635975,"version":"3.56.0"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3496543","type":"journal-article","created":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T18:44:26Z","timestamp":1731437066000},"page":"167262-167277","source":"Crossref","is-referenced-by-count":8,"title":["Multi-Spectral and Multi-Temporal Features Fusion With SE Network for Anomalous Sound Detection"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8197-176X","authenticated-orcid":false,"given":"Dewei","family":"Kong","sequence":"first","affiliation":[{"name":"Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongjiang","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4737-1340","authenticated-orcid":false,"given":"Guoshun","family":"Yuan","sequence":"additional","affiliation":[{"name":"Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.5815\/ijem.2016.04.01"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.20965\/ijat.2017.p0004"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2018.01.002"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2022.112351"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2015.11.016"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3409350"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3294334"},{"key":"ref8","article-title":"Description and discussion on DCASE2020 challenge task2: Unsupervised anomalous sound detection for machine condition monitoring","author":"Koizumi","year":"2020","journal-title":"arXiv:2006.05822"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP.2017.8168164"},{"key":"ref10","article-title":"Anomalous sound detection with machine learning: A systematic review","author":"Nunes","year":"2021","journal-title":"arXiv:2102.07820"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9054344"},{"key":"ref12","article-title":"ID-conditioned auto-encoder for unsupervised anomaly detection","author":"Kapka","year":"2020","journal-title":"arXiv:2007.05314"},{"key":"ref13","first-page":"2","article-title":"An ensemble approach to unsupervised anomalous sound detection","volume-title":"Proc. DCASE","author":"Alam"},{"key":"ref14","article-title":"Ensemble of auto-encoder based systems for anomaly detection","author":"Daniluk","year":"2020"},{"key":"ref15","article-title":"Conformer-based id-aware autoencoder for unsupervised anomalous sound detection","author":"Hayashi","year":"2020"},{"key":"ref16","article-title":"Unsupervised detection of anomalous machine sound using various spectral features and focused hypothesis test in the reverberant and noisy environment","author":"Park","year":"2020"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2018.2877258"},{"key":"ref18","first-page":"46","article-title":"Self-supervised classification for detecting anomalous sounds","volume-title":"Proc. 5th Workshop Detection Classification Acoust. Scenes Events (DCASE)","author":"Giri"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10096742"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10447764"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9414662"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10095568"},{"key":"ref23","first-page":"10215","article-title":"Glow: Generative flow with invertible 1\u00d71 convolutions","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Kingma"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747868"},{"key":"ref25","first-page":"2335","article-title":"Masked autoregressive flow for density estimation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Papamakarios"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.apacoust.2022.109188"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TASSP.1980.1163420"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2023-2416"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00482"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-97909-0_46"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10096054"},{"key":"ref33","article-title":"Robust anomaly sound detection framework for machine condition monitoring","author":"Zeng","year":"2022"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9534290"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10097176"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.21437\/SSW.2016"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1214301"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4842-6168-2_6"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01108"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2023.3337153"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.48550\/arxiv.1710.09412"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2938007"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2022.107882"},{"key":"ref45","doi-asserted-by":"crossref","DOI":"10.1016\/j.dsp.2020.102943","article-title":"Robust acoustic scene classification using a multi-spectrogram encoder\u2013decoder framework","volume":"110","author":"Pham","year":"2021","journal-title":"Digit. Signal Process."},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICSDA.2017.8384446"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/WASPAA.2019.8937164"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.33682\/m76f-d618"},{"key":"ref49","article-title":"Comparison performance of spectrogram and scalogram as input of acoustic recognition task","author":"Phan","year":"2024","journal-title":"arXiv:2403.03611"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10447924"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10380310\/10750805.pdf?arnumber=10750805","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T15:22:51Z","timestamp":1732720971000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10750805\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3496543","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}