标题/作者	年份
Micronets: Neural network architectures for deploying tinyml applications on commodity microcontrollers C Banbury, C Zhou, I Fedorov, R Matas, U Thakker, D Gope, ... Proceedings of Machine Learning and Systems 3, 517-532	2021
Description and discussion on DCASE2020 challenge task2: Unsupervised anomalous sound detection for machine condition monitoring Y Koizumi, Y Kawaguchi, K Imoto, T Nakamura, Y Nikaido, R Tanabe, ... arXiv preprint arXiv:2006.05822	2020
ToyADMOS2: Another dataset of miniature-machine operating sounds for anomalous sound detection under domain shift conditions N Harada, D Niizumi, D Takeuchi, Y Ohishi, M Yasuda, S Saito arXiv preprint arXiv:2106.02369	2021
Mlperf tiny benchmark C Banbury, VJ Reddi, P Torelli, J Holleman, N Jeffries, C Kiraly, P Montino, ... arXiv preprint arXiv:2106.07597	2021
Anomalous sound detection based on interpolation deep neural network K Suefusa, T Nishida, H Purohit, R Tanabe, T Endo, Y Kawaguchi ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …	2020
MIMII DUE: Sound dataset for malfunctioning industrial machine investigation and inspection with domain shifts due to changes in operational and environmental conditions R Tanabe, H Purohit, K Dohi, T Endo, Y Nikaido, T Nakamura, ... 2021 IEEE Workshop on Applications of Signal Processing to Audio and …	2021
MIMII DG: Sound dataset for malfunctioning industrial machine investigation and inspection for domain generalization task K Dohi, T Nishida, H Purohit, R Tanabe, T Endo, M Yamamoto, Y Nikaido, ... arXiv preprint arXiv:2205.13879	2022
Unsupervised anomalous sound detection using self-supervised classification and group masked autoencoder for density estimation R Giri, SV Tenneti, K Helwani, F Cheng, U Isik, A Krishnaswamy Challenge on Detection and Classification of Acoustic Scenes and Events …	2020
A comprehensive review of polyphonic sound event detection TK Chan, CS Chin IEEE Access 8, 103339-103373	2020
Self-supervised classification for detecting anomalous sounds R Giri, SV Tenneti, F Cheng, K Helwani, U Isik, A Krishnaswamy	2020
Fog-based intelligent machine malfunction monitoring system for industry 4.0 BV Natesha, RMR Guddeti IEEE Transactions on Industrial Informatics 17 (12), 7923-7932	2021
Machine learning for microcontroller-class hardware-a review SS Saha, SS Sandha, M Srivastava IEEE Sensors Journal	2022
Acoustic anomaly detection for machine sounds based on image transfer learning R Müller, F Ritz, S Illium, C Linnhoff-Popien arXiv preprint arXiv:2006.03429	2020
Reframing unsupervised machine condition monitoring as a supervised classification task with outlier-exposed classifiers P Primus Tech. Rep., DCASE2020 Challenge	2020
Anomalous sound detection as a simple binary classification problem with careful selection of proxy outlier examples P Primus, V Haunschmid, P Praher, G Widmer arXiv preprint arXiv:2011.02949	2020
Acoustic anomaly detection of mechanical failures in noisy real-life factory environments Y Tagawa, R Maskeliūnas, R Damaševičius Electronics 10 (19), 2329	2021
Detection of Anomalous Sounds for Machine Condition Monitoring using Classification Confidence. T Inoue, P Vinayavekhin, S Morikuni, S Wang, TH Trong, D Wood, ... DCASE, 66-70	2020
Deep dense and convolutional autoencoders for unsupervised anomaly detection in machine condition sounds A Ribeiro, LM Matos, PJ Pereira, EC Nunes, AL Ferreira, P Cortez, ... arXiv preprint arXiv:2006.10417	2020
Fully learnable deep wavelet transform for unsupervised monitoring of high-frequency time series G Michau, G Frusque, O Fink Proceedings of the National Academy of Sciences 119 (8), e2106598119	2022
Spidernet: Attention network for one-shot anomaly detection in sounds Y Koizumi, M Yasuda, S Murata, S Saito, H Uematsu, N Harada ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …	2020

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