File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

이승준

Lee, Seung Jun
Nuclear Safety Assessment and Plant HMI Evolution Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Full metadata record

DC Field Value Language
dc.citation.conferencePlace UK -
dc.citation.title ESREL2022 -
dc.contributor.author Cho, Seung Gyu -
dc.contributor.author Lee, Seung Jun -
dc.date.accessioned 2023-12-29T12:05:09Z -
dc.date.available 2023-12-29T12:05:09Z -
dc.date.created 2023-12-29 -
dc.date.issued 2022-08-30 -
dc.identifier.bibliographicCitation ESREL2022 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/67318 -
dc.identifier.url https://easychair.org/smart-program/ESREL2022/2022-08-30.html#talk:200340 -
dc.language 영어 -
dc.publisher ESREL -
dc.title A Deep Support Vector Data Description Model for Abnormality Detection and Application with Abnormality Classification in a Nuclear Power Plant -
dc.type Conference Paper -
dc.date.conferenceDate 2022-08-28 -

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.