@article{527a6e041fb64008af9526400eddf9a2,
title = "Anomaly Detection in Binary Time Series Data: An unsupervised Machine Learning Approach for Condition Monitoring",
keywords = "Anomaly Detection, Binary Time Series Data, Data-driven Maintenance, Smart Manufacturing, Unsupervised Machine Learning",
author = "G{\'a}bor Princz and Masoud Shaloo and Selim Erol",
note = "Publisher Copyright: {\textcopyright} 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0); 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 ; Conference date: 22-11-2023 Through 24-11-2023",
year = "2024",
doi = "10.1016/j.procs.2024.01.105",
language = "English",
volume = "232",
pages = "1065--1078",
journal = "Procedia Computer Science",
issn = "1877-0509",
}