학술논문
A novel self-training semi-supervised deep learning approach for machinery fault diagnosis.
Document Type
Article
Author
Source
International Journal of Production Research; Dec2023, Vol. 61 Issue 23, p8238-8251, 14p
Subject
Language
ISSN
00207543
Abstract
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)