{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T07:44:05Z","timestamp":1776152645134,"version":"3.50.1"},"reference-count":111,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["2159382"],"award-info":[{"award-number":["2159382"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Unilever U.K. Ltd."},{"DOI":"10.13039\/501100020624","name":"NIHR Nottingham Biomedical Research Centre","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100020624","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1109\/tpami.2023.3325770","type":"journal-article","created":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T17:47:47Z","timestamp":1697651267000},"page":"805-822","source":"Crossref","is-referenced-by-count":43,"title":["COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognition"],"prefix":"10.1109","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3678-7541","authenticated-orcid":false,"given":"Mani Kumar","family":"Tellamekala","sequence":"first","affiliation":[{"name":"Computer Vision Lab, School of Computer Science, University of Nottingham, Nottingham, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1129-8223","authenticated-orcid":false,"given":"Shahin","family":"Amiriparian","sequence":"additional","affiliation":[{"name":"Chair of Embedded Intelligence for Health Care & Wellbeing, University of Augsburg, Augsburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6478-8699","authenticated-orcid":false,"given":"Bj\u00f6rn W.","family":"Schuller","sequence":"additional","affiliation":[{"name":"Chair of Embedded Intelligence for Health Care & Wellbeing, University of Augsburg, Augsburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2367-162X","authenticated-orcid":false,"given":"Elisabeth","family":"Andr\u00e9","sequence":"additional","affiliation":[{"name":"Chair for Human-Centered Artificial Intelligence, University of Augsburg, Augsburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5545-6895","authenticated-orcid":false,"given":"Timo","family":"Giesbrecht","sequence":"additional","affiliation":[{"name":"Unilever R&D Port Sunlight, Wirral, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2414-161X","authenticated-orcid":false,"given":"Michel","family":"Valstar","sequence":"additional","affiliation":[{"name":"Computer Vision Lab, School of Computer Science, University of Nottingham, Nottingham, U.K."}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-05946-3"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2388676.2388776"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2512530.2512533"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3347320.3357688"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2682899"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2011.9"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.52"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2018.2890471"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2017.2713783"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2021.03.007"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2021.3135152"},{"key":"ref12","article-title":"Packed-ensembles for efficient uncertainty estimation","author":"Laurent"},{"key":"ref13","first-page":"1321","article-title":"On calibration of modern neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Guo"},{"key":"ref14","first-page":"15288","article-title":"Calibrating deep neural networks using focal loss","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Mukhoti"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298640"},{"key":"ref16","article-title":"Intriguing properties of neural networks","author":"Szegedy"},{"key":"ref17","first-page":"2805","article-title":"Trainable calibration measures for neural networks from kernel mean embeddings","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kumar"},{"key":"ref18","first-page":"7034","article-title":"Confidence-aware learning for deep neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Moon"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.538"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10579-008-9076-6"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/p18-1208"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2011.5771357"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3423327.3423673"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3475957.3484450"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3551876.3554817"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/FG47880.2020.00126"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00408"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01424"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19836-6_9"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.02.003"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.06.019"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2021.3106895"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00618"},{"key":"ref34","first-page":"17616","article-title":"Relative uncertainty learning for facial expression recognition","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00693"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ACII52823.2021.9597425"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/11573548_123"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2013.6607464"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3133944.3133952"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00896"},{"key":"ref41","first-page":"3390","article-title":"Stochastic process regression for cross-cultural speech emotion recognition","volume-title":"Proc. Interspeech","author":"Mani Kumar","year":"2021"},{"key":"ref42","first-page":"1704","article-title":"Conditional neural processes","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Garnelo"},{"key":"ref43","article-title":"Neural processes","author":"Garnelo"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2022.3157141"},{"key":"ref45","first-page":"67","article-title":"Extended confidence-weighted averaging in sensor fusion","volume-title":"Proc. Junior Scientist Conf.","author":"Sch\u00f6rgendorfer"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/1459359.1459513"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2008.2011515"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00640"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197266"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00062"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19836-6_12"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9534161"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i06.6597"},{"key":"ref54","first-page":"11809","article-title":"Rethinking calibration of deep neural networks: Do not be afraid of overconfidence","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref55","first-page":"15682","article-title":"Revisiting the calibration of modern neural networks","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Minderer"},{"key":"ref56","first-page":"609","article-title":"Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zadrozny"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1145\/775107.775151"},{"key":"ref58","first-page":"61","article-title":"Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods","volume-title":"Proc. Adv. Large Margin Classifiers","author":"Platt"},{"key":"ref59","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref60","first-page":"18237","article-title":"Improving model calibration with accuracy versus uncertainty optimization","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Krishnan"},{"key":"ref61","first-page":"2796","article-title":"Accurate uncertainties for deep learning using calibrated regression","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kuleshov"},{"key":"ref62","first-page":"5897","article-title":"Distribution calibration for regression","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Song"},{"key":"ref63","article-title":"Quantile regularization: Towards implicit calibration of regression models","author":"Utpala","year":"2020"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01368"},{"key":"ref65","first-page":"2898","article-title":"Addressing failure prediction by learning model confidence","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Corbi\u00e8re"},{"key":"ref66","article-title":"Are out-of-distribution detection methods effective on large-scale datasets?","author":"Roady","year":"2019"},{"key":"ref67","first-page":"4878","article-title":"Selective classification for deep neural networks","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Geifman"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2798607"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2719043"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2016.2635124"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2014.11.007"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2017.2764438"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2013.2267205"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00610"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1145\/3341981.3344221"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00575"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2944808"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2018-1477"},{"key":"ref79","article-title":"Multi-modal emotion recognition on IEMOCAP with neural networks","author":"Tripathi","year":"2018"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.417"},{"key":"ref81","first-page":"269","article-title":"Modality-transferable emotion embeddings for low-resource multimodal emotion recognition","volume-title":"Proc. Conf. Empir. Methods Natural Lang. Joint Conf. Natural Lang. Process.","author":"Dai"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.2307\/2532051"},{"key":"ref83","first-page":"7136","article-title":"AMOA: Global acoustic feature enhanced modal-order-aware network for multimodal sentiment analysis","volume-title":"Proc. 29th Int. Conf. Comput. Linguistics","author":"Li"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.772"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6953"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-00280-0"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2021.3061605"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2017.2740923"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1145\/3347320.3357690"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952132"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1145\/3133944.3133949"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-2680"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853739"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref95","article-title":"SGDR: Stochastic gradient descent with warm restarts","author":"Loshchilov"},{"key":"ref96","article-title":"Adam: A method for stochastic optimization","author":"Kingma"},{"key":"ref97","article-title":"Tune: A research platform for distributed model selection and training","author":"Liaw","year":"2018"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1145\/3347320.3357692"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1656"},{"key":"ref100","article-title":"Masked face recognition for secure authentication","author":"Anwar","year":"2020"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/TBC.2022.3215245"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413678"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2013.2250954"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1145\/3606039.3613114"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33017216"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33016892"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/p18-1209"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d17-1115"},{"key":"ref109","article-title":"Learning factorized multimodal representations","author":"Tsai"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6431"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.18653\/vl\/N19-142"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10384454\/10287630.pdf?arnumber=10287630","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T04:31:05Z","timestamp":1705033865000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10287630\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2]]},"references-count":111,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2023.3325770","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2]]}}}