{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T07:31:52Z","timestamp":1780471912226,"version":"3.54.1"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2019A1515011181"],"award-info":[{"award-number":["2019A1515011181"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Innovation Commission of Shenzhen","award":["JCYJ20190808162613130"],"award-info":[{"award-number":["JCYJ20190808162613130"]}]},{"name":"Shenzhen High-Level Talents Program"},{"name":"Open Research Fund from Guangdong Laboratory of Artificial Intelligence & Digital Economy","award":["GML-KF-22-28"],"award-info":[{"award-number":["GML-KF-22-28"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Affective Comput."],"published-print":{"date-parts":[[2023,7,1]]},"DOI":"10.1109\/taffc.2022.3170369","type":"journal-article","created":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T19:37:29Z","timestamp":1651001849000},"page":"2048-2063","source":"Crossref","is-referenced-by-count":113,"title":["GANSER: A Self-Supervised Data Augmentation Framework for EEG-Based Emotion Recognition"],"prefix":"10.1109","volume":"14","author":[{"given":"Zhi","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4242-4840","authenticated-orcid":false,"given":"Yan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7524-5999","authenticated-orcid":false,"given":"Sheng-hua","family":"Zhong","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-55394-8_1"},{"key":"ref2","volume-title":"The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind","author":"Minsky","year":"2007"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2020.2994159"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ab260c"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2020.108885"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7533048"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2951728"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2863267"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2018.2817622"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2020.3013711"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2020.3025777"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2017.2768030"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2021.3051332"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2017.2788081"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM.2016.7822545"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.14569\/IJACSA.2018.090843"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8461315"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC44109.2020.9176301"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2019.2937768"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3061094"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-04221-9_25"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2017.8036864"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2404941"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-73600-6_8"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/abb580"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2018.8512865"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-22796-8_16"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/BHI.2018.8333379"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8852347"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8852227"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2020.00015"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9206942"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489331"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2905157"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jestch.2021.03.012"},{"key":"ref36","first-page":"5767","article-title":"Improved training of wasserstein GANs","volume-title":"Proc. Int. Conf. Neural Inf. Process.","author":"Gulrajani"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.4324\/9781410605337-29"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2496141"},{"issue":"1","key":"ref40","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2011.15"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2017.2688239"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/NER.2013.6695876"},{"key":"ref44","first-page":"8026","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Int. Conf. Neural Inf. Process.","author":"Paszke"},{"key":"ref45","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2020.2976112"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1515\/bmt-2019-0306"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICDSE47409.2019.8971484"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9206750"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-91415-8_39"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.08.018"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2020.10.004"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46672-9_58"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.14569\/IJACSA.2017.081046"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106954"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350871"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106243"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5599615"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2017.2712143"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-019-00860-w"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2020.00043"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2978163"},{"issue":"11","key":"ref63","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":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3012900"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2019.2906824"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-04239-4_39"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.2995767"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TENCON.2016.7848034"}],"container-title":["IEEE Transactions on Affective Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5165369\/10254612\/09763358.pdf?arnumber=9763358","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T22:15:04Z","timestamp":1705961704000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9763358\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,1]]},"references-count":68,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/taffc.2022.3170369","relation":{},"ISSN":["1949-3045","2371-9850"],"issn-type":[{"value":"1949-3045","type":"electronic"},{"value":"2371-9850","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,1]]}}}