{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T22:23:24Z","timestamp":1781735004632,"version":"3.54.5"},"reference-count":58,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Affective Comput."],"published-print":{"date-parts":[[2021,4,1]]},"DOI":"10.1109\/taffc.2018.2873600","type":"journal-article","created":{"date-parts":[[2018,10,4]],"date-time":"2018-10-04T19:46:28Z","timestamp":1538682388000},"page":"363-376","source":"Crossref","is-referenced-by-count":35,"title":["Deep Learning for Spatio-Temporal Modeling of Dynamic Spontaneous Emotions"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6258-6970","authenticated-orcid":false,"given":"Dawood","family":"Al Chanti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alice","family":"Caplier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","author":"xingjian","year":"2015","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref33","article-title":"Layer normalization","author":"ba","year":"2016","journal-title":"Neural Inf Process Syst"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.59"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10578-9_23"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.5121\/ijma.2013.5505"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"key":"ref36","first-page":"115","article-title":"Learning precise timing with LSTM recurrent networks","volume":"3","author":"gers","year":"2002","journal-title":"J Mach Learn Res"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/0893-9659(91)90080-F"},{"key":"ref34","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":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2005.1521424"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/AFGR.2000.840611"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2013.4"},{"key":"ref2","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/1140.001.0001","author":"picard","year":"1997","journal-title":"Affective Computing"},{"key":"ref1","author":"goleman","year":"2006","journal-title":"Emotional Intelligence"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1023\/B:JOBA.0000007455.08539.94"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-57021-1_1"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206744"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477450"},{"key":"ref23","article-title":"Multi-modality fusion based on consensus-voting and 3D convolution for isolated gesture recognition","author":"duan","year":"2016"},{"key":"ref26","first-page":"30","article-title":"Facial expression recognition using enhanced deep 3D convolutional neural networks","author":"mohammad mahoor","year":"2017","journal-title":"Proc IEEE Conf Comp Vis Pattern Recognit"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s12193-015-0195-2"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/1291233.1291311"},{"key":"ref51","article-title":"Histograms of oriented gradients for 3D object retrieval","author":"scherer","year":"2010","journal-title":"Eur Comput Graph Visualization Comput Vis"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2017.05.218"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2014.03.006"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2331141"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2008.08.005"},{"key":"ref54","first-page":"143","article-title":"Deeply learning deformable facial action parts model for dynamic expression analysis","author":"liu","year":"2014","journal-title":"Proc Asian Conf Comput Vis"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/s00138-015-0677-y"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2003.1238354"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.5220\/0006118000640074"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/S0301-0511(03)00098-X"},{"key":"ref40","article-title":"Digital image processing","volume":"14","author":"masters","year":"2009","journal-title":"J Biomed Opt"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.4236\/psych.2013.48094"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1098\/rstb.2009.0135"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.93"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/FGR.2006.108"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1110"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2005.09.011"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-13772-3_41"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.5244\/C.24.13"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1037\/0003-066X.48.4.384"},{"key":"ref3","first-page":"19","article-title":"Expression and the nature of emotion","volume":"3","author":"ekman","year":"1984","journal-title":"Approaches Emotion"},{"key":"ref6","first-page":"4039","article-title":"Differentiating between posed and spontaneous expressions with latent regression Bayesian network","author":"gan","year":"2017","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref5","author":"ekman","year":"1997"},{"key":"ref8","first-page":"1108","article-title":"Posed and spontaneous expression distinguishment from infrared thermal images","author":"liu","year":"2012","journal-title":"Proc 21st Int Conf Pattern Recognit"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1080\/02699931.2017.1320978"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299007"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ACII.2013.20"},{"key":"ref46","article-title":"Visually debugging restricted Boltzmann machine training with a 3D example","author":"yosinski","year":"2012","journal-title":"Proc 29th Int Conf Mach Learn Representation Learn Workshop"},{"key":"ref45","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"2010","journal-title":"Proc 13th Int Conf Artif Intell Statist"},{"key":"ref48","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref47","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.68"},{"key":"ref44","first-page":"13","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"International Conference on Learning Representations (ICLR)"},{"key":"ref43","first-page":"265","article-title":"Tensorflow: A system for large-scale machine learning","author":"abadi","year":"0","journal-title":"Proc 12th USENIX Symp Operating Syst Design Implementation (OSDI 16)"}],"container-title":["IEEE Transactions on Affective Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5165369\/9443045\/08481451.pdf?arnumber=8481451","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T01:23:02Z","timestamp":1720660982000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8481451\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,1]]},"references-count":58,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/taffc.2018.2873600","relation":{},"ISSN":["1949-3045","2371-9850"],"issn-type":[{"value":"1949-3045","type":"electronic"},{"value":"2371-9850","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,1]]}}}