{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T20:09:03Z","timestamp":1770840543952,"version":"3.50.1"},"reference-count":27,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100003725","name":"Basic Research Program through the National Research Foundation of Korea","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003621","name":"Ministry of Science and ICT","doi-asserted-by":"publisher","award":["2019R1A4A1021702"],"award-info":[{"award-number":["2019R1A4A1021702"]}],"id":[{"id":"10.13039\/501100003621","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010418","name":"Institute of Information & Communications Technology Promotion","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010418","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Korea Government, MSIT","award":["2019-0-00374"],"award-info":[{"award-number":["2019-0-00374"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3100419","type":"journal-article","created":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T21:48:32Z","timestamp":1627336112000},"page":"124549-124559","source":"Crossref","is-referenced-by-count":34,"title":["Deep Learning-Based Anomaly Detection to Classify Inaccurate Data and Damaged Condition of a Cable-Stayed Bridge"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8352-1631","authenticated-orcid":false,"given":"Hyesook","family":"Son","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7745-1158","authenticated-orcid":false,"given":"Yun","family":"Jang","sequence":"additional","affiliation":[]},{"given":"Seung-Eock","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Dongjoo","family":"Kim","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5899-7769","authenticated-orcid":false,"given":"Jong-Woong","family":"Park","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2016.10.033"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s13349-016-0160-0"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.21629\/JSEE.2018.04.22"},{"key":"ref13","first-page":"1","article-title":"LSTM-based encoder-decoder for multi-sensor anomaly detection","volume":"abs 1607 148","author":"malhotra","year":"2016","journal-title":"CoRR"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011409"},{"key":"ref15","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","volume":"28","author":"shi","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1177\/1475921718757405"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1002\/stc.2296"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1177\/1475921720924601"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1111\/mice.12528"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)EM.1943-7889.0000982"},{"key":"ref27","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume":"32","author":"paszke","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.jsv.2005.06.016"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-008-0371-9"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)ST.1943-541X.0001218"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/FSKD.2008.244"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2010.021510.00088"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2018.11.027"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/EAIT.2011.25"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1117\/12.880513"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2019.106495"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1002\/stc.1998"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1002\/stc.2136"},{"key":"ref24","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","author":"sutskever","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref26","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc 3rd Int Conf Learn Represent (ICLR)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.engstruct.2017.09.063"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09497115.pdf?arnumber=9497115","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:57:14Z","timestamp":1639771034000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9497115\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3100419","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}