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We employ a Top-K clustering objective for separating the latent space, selecting the most discriminative features from the latent space. We use the approach to the benchmark Tennessee Eastman data set to prove its applicability. We provide different ablation studies and analyze the method concerning various downstream tasks, including anomaly detection, binary and multi-class classification. The obtained results show the potential of the approach to improve downstream tasks compared to standard autoencoder architectures.<\/jats:p>","DOI":"10.3390\/s21165488","type":"journal-article","created":{"date-parts":[[2021,8,15]],"date-time":"2021-08-15T22:51:27Z","timestamp":1629067887000},"page":"5488","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Deep Convolutional Clustering-Based Time Series Anomaly Detection"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9374-9074","authenticated-orcid":false,"given":"Gavneet Singh","family":"Chadha","sequence":"first","affiliation":[{"name":"Department of Automation Technology, South Westphalia University of Applied Sciences, 59494 Soest, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Intekhab","family":"Islam","sequence":"additional","affiliation":[{"name":"Department of Automation Technology, South Westphalia University of Applied Sciences, 59494 Soest, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Schwung","sequence":"additional","affiliation":[{"name":"Department of Automation Technology, South Westphalia University of Applied Sciences, 59494 Soest, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steven X.","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Automatic Control and Complex Systems, University of Duisburg-Essen, 47057 Duisburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.isatra.2020.07.011","article-title":"Bidirectional deep recurrent neural networks for process fault classification","volume":"106","author":"Chadha","year":"2020","journal-title":"ISA Trans."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2233","DOI":"10.1109\/TII.2014.2300753","article-title":"Internet of things in industries: A survey","volume":"10","author":"He","year":"2014","journal-title":"IEEE Trans. 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