{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:20:32Z","timestamp":1740169232080,"version":"3.37.3"},"reference-count":47,"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":[{"name":"National Training Program of Innovation and Entrepreneurship for Undergraduates of China","award":["201910708024"],"award-info":[{"award-number":["201910708024"]}]},{"name":"Research Plan of Shaanxi Provincial Department of Education","award":["15JK1086"],"award-info":[{"award-number":["15JK1086"]}]},{"DOI":"10.13039\/501100008250","name":"Shaanxi University of Science and Technology Ph.D. Project","doi-asserted-by":"publisher","award":["BJ14-07"],"award-info":[{"award-number":["BJ14-07"]}],"id":[{"id":"10.13039\/501100008250","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3068921","type":"journal-article","created":{"date-parts":[[2021,3,24]],"date-time":"2021-03-24T19:45:17Z","timestamp":1616615117000},"page":"48704-48712","source":"Crossref","is-referenced-by-count":2,"title":["Parameter-Free Attention in fMRI Decoding"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4930-5978","authenticated-orcid":false,"given":"Yong","family":"Qi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2965-3158","authenticated-orcid":false,"given":"Huawei","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4469-0173","authenticated-orcid":false,"given":"Yanping","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4916-3025","authenticated-orcid":false,"given":"Jiashu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-42054-2_55"},{"key":"ref38","first-page":"924","article-title":"Deep learning made easier by linear transformations in perceptrons","author":"raiko","year":"2012","journal-title":"Proc Artif Intell Statist"},{"journal-title":"Modern Applied Statistics with S-Plus","year":"2013","author":"venables","key":"ref33"},{"journal-title":"Pattern Recognition and Neural Networks","year":"2007","author":"ripley","key":"ref32"},{"key":"ref31","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","author":"bishop","year":"1995","journal-title":"Neural Networks for Pattern Recognition"},{"key":"ref30","article-title":"Parameter-free spatial attention network for person re-identification","author":"wang","year":"2018","journal-title":"arXiv 1811 12150"},{"key":"ref37","article-title":"Accelerated gradient descent by factor-centering decomposition","volume":"98","author":"schraudolph","year":"1998"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-49430-8_11"},{"key":"ref35","first-page":"562","article-title":"Deeply-supervised nets","author":"lee","year":"2015","journal-title":"Proc Artif Intell Statist"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.112.2.291"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref11","first-page":"25","author":"zhang","year":"2013","journal-title":"Background of Visual Attention&#x2014;Theory and Experiments"},{"journal-title":"1200 subjects data release reference manual","year":"2017","author":"wu-minn","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2014.2369495"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.05.033"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3203217.3203239"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.06.034"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-018-6146-7"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.neuro.23.1.315"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.ne.18.030195.001205"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.683"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.24891"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58548-8_7"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/PRNI.2018.8423964"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00813"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2865280"},{"key":"ref5","article-title":"Interpretable LSTMs for whole-brain neuroimaging analyses","author":"thomas","year":"2018","journal-title":"arXiv 1810 09945"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00314"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363838"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.97.4.523"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2907040"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-67159-8_9"},{"key":"ref20","first-page":"2204","article-title":"Recurrent models of visual attention","author":"mnih","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-41501-7_25"},{"key":"ref22","first-page":"577","article-title":"Attention-based models for speech recognition","author":"chorowski","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2915988"},{"key":"ref21","article-title":"Neural machine translation by jointly learning to align and translate","author":"bahdanau","year":"2014","journal-title":"arXiv 1409 0473"},{"key":"ref42","article-title":"Deep learning of fMRI big data: A novel approach to subject-transfer decoding","author":"koyamada","year":"2015","journal-title":"arXiv 1502 00093"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.557"},{"key":"ref41","article-title":"Grad-CAM: Why did you say that?","author":"selvaraju","year":"2016","journal-title":"arXiv 1611 07450"},{"key":"ref23","first-page":"2048","article-title":"Show, attend and tell: Neural image caption generation with visual attention","author":"xu","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1126\/science.1136800"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.349"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32695-1_7"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.145"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09386094.pdf?arnumber=9386094","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T19:27:22Z","timestamp":1724700442000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9386094\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3068921","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2021]]}}}