{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T06:28:15Z","timestamp":1772778495665,"version":"3.50.1"},"reference-count":72,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"crossref"}]},{"name":"US Office of Naval Research Global under Cooperative","award":["ONRG - NICOP - N62909-19-1-2058"],"award-info":[{"award-number":["ONRG - NICOP - N62909-19-1-2058"]}]},{"name":"AFOSR _ DST Australian Autonomy Initiative","award":["ID10134"],"award-info":[{"award-number":["ID10134"]}]},{"name":"NSW Defence Innovation Network and NSW State Government of Australia","award":["PP21-22.03.02"],"award-info":[{"award-number":["PP21-22.03.02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Emerg. Top. Comput. Intell."],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1109\/tetci.2023.3268707","type":"journal-article","created":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T14:33:19Z","timestamp":1683729199000},"page":"1362-1376","source":"Crossref","is-referenced-by-count":2,"title":["Preference Neural Network"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3381-4708","authenticated-orcid":false,"given":"Ayman","family":"Elgharabawy","sequence":"first","affiliation":[{"name":"Biological Data Science Institute (BDSI), College of Science, Australian National University, Canberra, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7745-9667","authenticated-orcid":false,"given":"Mukesh","family":"Prasad","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, School of Computer Science, FEIT, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8371-8197","authenticated-orcid":false,"given":"Chin-Teng","family":"Lin","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, School of Computer Science, FEIT, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3225106"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.07.001"},{"key":"ref12","article-title":"User ocean personality model construction method using a BP neural network","volume":"11","author":"qin","year":"2022","journal-title":"Electron"},{"key":"ref56","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1007\/s10994-018-5743-z","article-title":"Discovering a Taste for the Unusual: Exceptional Models for Preference Mining","volume":"107","author":"s\u00e1","year":"2018","journal-title":"Mach Learn"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-39857-8_15"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.4304\/jcp.9.3.557-565"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-013-5374-3"},{"key":"ref53","article-title":"MNIST handwritten digit database","author":"lecun","year":"2010"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553395"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2022.02.002"},{"key":"ref55","author":"meshkini","year":"2019","journal-title":"An Analysis of Convolutional Neural Network for Fashion Images Classification (Fashion-MNIST)"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3233481"},{"key":"ref54","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-36169-3_29"},{"key":"ref16","author":"f\u00fcrnkranz","year":"2010","journal-title":"Preference Learning"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-14125-6"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2008.08.002"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.2307\/1412159"},{"key":"ref50","article-title":"Rank correlation methods","author":"govindarajulu","year":"2012","journal-title":"Technometrics"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3057719"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.3390\/app13053082"},{"key":"ref48","article-title":"Preference neural network convergence performance","author":"elgharabawy","year":"2020"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/6912315"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.3390\/e22101174"},{"key":"ref41","first-page":"1","article-title":"Robust visual saliency optimization based on bidirectional Markov chains","volume":"13","author":"jiang","year":"2020","journal-title":"Cogn Comput"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2021.109766"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2020.103345"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2000.861344"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1093\/comjnl\/bxaa168"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2022.3148411"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3162301"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1023\/A:1022850703159","volume":"19","author":"montaner","year":"2003","journal-title":"Artif Intell Rev"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"ref6","first-page":"641","article-title":"Pranking With Ranking","author":"crammer","year":"0","journal-title":"Proc IEEE 14th Int Conf Neural Inf Process Syst Natural Synthetic"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2005.11"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1049\/cit2.12174"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3390\/rs13224604"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1029\/2022WR033241"},{"key":"ref37","author":"aizenberg","year":"2000","journal-title":"Multi-Valued and Universal Binary Neurons Theory Learning and Applications"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ISMVL.1999.779692"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3007130"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-19-1559-8_27"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3225782"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3468506"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v30i1.2114"},{"key":"ref1","author":"frnkranz","year":"2010","journal-title":"Preference Learning"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3237740"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2019.2957386"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/ISKE.2017.8258754"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/IEMCON.2018.8615011"},{"key":"ref72","article-title":"Mathematica","year":"2022"},{"key":"ref24","first-page":"933","article-title":"An efficient boosting algorithm for combining preferences","volume":"4","author":"freund","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref68","article-title":"Preference neural network source code","author":"elgharabawy","year":"2022"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33266-1_4"},{"key":"ref67","article-title":"Label ranking forests","volume":"34","author":"s\u00e1","year":"2017","journal-title":"Expert Systems Int J of Knowledge Eng"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2019.00311"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-009-9112-1"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-34879-3_2"},{"key":"ref20","first-page":"143","article-title":"Instance-Based Label Ranking Using the Mallows Model","author":"cheng","year":"0","journal-title":"Proc ECCBR Workshops"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00009"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00012"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102363"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412221"},{"key":"ref21","article-title":"Learning from pairwise preference data using gaussian mixture model","volume":"33","author":"grbovic","year":"2012","journal-title":"Preference Learn Problems Appl AI"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1117\/12.2639667"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2991527"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-019-01026-0"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899X\/1130\/1\/012084"},{"key":"ref60","first-page":"87.1","article-title":"Wide residual networks","author":"zagoruyko","year":"0","journal-title":"Proc Brit Mach Vis Conf (BMVC)"},{"key":"ref62","first-page":"10?096","article-title":"Efficientnetv2: Smaller models faster training","volume":"139","author":"tan","year":"0","journal-title":"Proc 38th Int Conf Mach Learn"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"}],"container-title":["IEEE Transactions on Emerging Topics in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7433297\/10261323\/10122200.pdf?arnumber=10122200","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T19:35:25Z","timestamp":1696880125000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10122200\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10]]},"references-count":72,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tetci.2023.3268707","relation":{},"ISSN":["2471-285X"],"issn-type":[{"value":"2471-285X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10]]}}}