@article {Tama:2020:0736-2935:5701,
title = "An overview of deep learning techniques for fault detection using vibration signal",
journal = "INTER-NOISE and NOISE-CON Congress and Conference Proceedings",
parent_itemid = "infobike://ince/incecp",
publishercode ="ince",
year = "2020",
volume = "261",
number = "1",
publication date ="2020-10-12T00:00:00",
pages = "5701-5706",
itemtype = "ARTICLE",
issn = "0736-2935",
url = "https://ince.publisher.ingentaconnect.com/content/ince/incecp/2020/00000261/00000001/art00079",
author = "Tama, Bayu Adhi and Lee, Soo Young and Lee, Seungchul",
abstract = "As a specialized sub-field of machine learning, deep learning has achieved tremendous implications in various real-world applications, and in noise and vibration engineering field is no exception. Deep learning has shown promising results with near-to-human-level accuracy. The objective
of this paper is to review and to explore the state-of-the-art deep learning techniques and their applications in noise and vibration engineering. Some relevant studies were carefully selected from publication indexing databases, resulting in a classification of existing studies into several
categories. This study reveals that some research fields in noise and vibration engineering were still underexplored. Therefore, we also provide some remaining research challenges and opportunities that require further investigation.",
}