{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T11:25:43Z","timestamp":1780658743992,"version":"3.54.1"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100003621","name":"Ministry of Science and Information and Communications Technologies (ICT) (MSIT), South Korea, Intelligent E-Nose Development for Gas Detection to Sub-ppb Level","doi-asserted-by":"publisher","award":["2020-0-01106"],"award-info":[{"award-number":["2020-0-01106"]}],"id":[{"id":"10.13039\/501100003621","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3185613","type":"journal-article","created":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T19:32:43Z","timestamp":1656012763000},"page":"68138-68150","source":"Crossref","is-referenced-by-count":5,"title":["Classifying Gas Data Measured Under Multiple Conditions Using Deep Learning"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9312-3904","authenticated-orcid":false,"given":"Hojung","family":"Lee","sequence":"first","affiliation":[{"name":"School of Integrated Technology, Yonsei University, Incheon, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaehui","family":"Hwang","sequence":"additional","affiliation":[{"name":"School of Integrated Technology, Yonsei University, Incheon, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6852-026X","authenticated-orcid":false,"given":"Hwin Dol","family":"Park","sequence":"additional","affiliation":[{"name":"Bio-Medical IT Convergence Research Division, Electronics and Telecommunications Research Institute, Daejeon, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2988-6955","authenticated-orcid":false,"given":"Jae Hun","family":"Choi","sequence":"additional","affiliation":[{"name":"Bio-Medical IT Convergence Research Division, Electronics and Telecommunications Research Institute, Daejeon, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8038-1119","authenticated-orcid":false,"given":"Jong-Seok","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Integrated Technology, Yonsei University, Incheon, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"New Portable Detector for Chemical Warfare Agents","year":"2021"},{"key":"ref2","volume-title":"E-Nose Station","year":"2021"},{"key":"ref3","volume-title":"Sensigent Chemical Sensing Technology","year":"2021"},{"key":"ref4","volume-title":"Operating Principle of Figaro Gas Sensors","year":"2021"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-4005(03)00321-6"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/s131014214"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/s7030267"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/S100302088"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1108\/02602280410525977"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-4005(03)00248-X"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/s16122069"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2005.858926"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/S0003-2670(97)00202-X"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IDAACS.2015.7340723"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2016.2619181"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.snb.2006.05.033"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1515\/mms-2015-0039"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2014.2361852"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.snb.2015.02.025"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2016.2574460"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.3390\/s18010157"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/MWSCAS.2018.8624038"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2892754"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3390\/s19010217"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/7184980"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1039\/C8RA02164C"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.snb.2013.05.027"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3038304"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.02.010"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/s130302967"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.3390\/s16010115"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3379336.3381482"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3267305.3267522"},{"key":"ref35","first-page":"1","article-title":"Multimodal deep learning","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","author":"Ngiam"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-017-0997-7"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3083486"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.3390\/electronics10070800"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.3390\/s21165452"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.12.024"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3341162.3344871"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2019.2901733"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2820903"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TAMD.2015.2449553"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/1101149.1101236"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.11.007"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.snb.2015.03.028"},{"key":"ref48","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref49","article-title":"Normalized mutual information to evaluate overlapping community finding algorithms","author":"McDaid","year":"2011","journal-title":"arXiv:1110.2515"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09804485.pdf?arnumber=9804485","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T05:33:45Z","timestamp":1706765625000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9804485\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3185613","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}