{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T02:32:47Z","timestamp":1778812367190,"version":"3.51.4"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2019,10,23]],"date-time":"2019-10-23T00:00:00Z","timestamp":1571788800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,10,23]],"date-time":"2019-10-23T00:00:00Z","timestamp":1571788800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872188"],"award-info":[{"award-number":["61872188"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1007\/s13042-019-01024-2","type":"journal-article","created":{"date-parts":[[2019,10,23]],"date-time":"2019-10-23T16:06:56Z","timestamp":1571846816000},"page":"779-793","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A discriminative deep association learning for facial expression recognition"],"prefix":"10.1007","volume":"11","author":[{"given":"Xing","family":"Jin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenyun","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4293-0869","authenticated-orcid":false,"given":"Zhong","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,23]]},"reference":[{"issue":"1","key":"1024_CR1","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1007\/s11042-015-3057-8","volume":"76","author":"M Wan","year":"2017","unstructured":"Wan M, Yang G, Gai S, Yang Z (2017) Two-dimensional discriminant locality preserving projections (2ddlpp) and its application to feature extraction via fuzzy set. Multimedia Tools Appl 76(1):355\u2013371","journal-title":"Multimedia Tools Appl"},{"key":"1024_CR2","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.ins.2014.02.145","volume":"274","author":"M Wan","year":"2014","unstructured":"Wan M, Li M, Yang G, Gai S, Jin Z (2014) Feature extraction using two-dimensional maximum embedding difference. Inf Sci 274:55\u201369","journal-title":"Inf Sci"},{"key":"1024_CR3","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.fss.2016.06.001","volume":"318","author":"M Wan","year":"2017","unstructured":"Wan M, Lai Z, Yang G, Yang Z, Zhang F, Zheng H (2017) Local graph embedding based on maximum margin criterion via fuzzy set. Fuzzy Sets Syst 318:120\u2013131","journal-title":"Fuzzy Sets Syst"},{"issue":"4","key":"1024_CR4","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1109\/TNNLS.2015.2422994","volume":"27","author":"Z Lai","year":"2015","unstructured":"Lai Z, Wong WK, Xu Y, Yang J, Zhang D (2015) Approximate orthogonal sparse embedding for dimensionality reduction. IEEE Trans Neural Netw Learn Syst 27(4):723\u2013735","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"10","key":"1024_CR5","doi-asserted-by":"publisher","first-page":"1942","DOI":"10.1109\/TNNLS.2013.2297381","volume":"25","author":"Z Lai","year":"2014","unstructured":"Lai Z, Xu Y, Chen Q, Yang J, Zhang D (2014) Multilinear sparse principal component analysis. IEEE Trans Neural Netw Learn Syst 25(10):1942\u20131950","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"1024_CR6","doi-asserted-by":"crossref","unstructured":"Kahou SE, Pal C, Bouthillier X, Froumenty P, G\u00fcl\u00e7ehre \u00c7, Memisevic R, Vincent P, Courville A, Bengio Y, Ferrari RC, et\u00a0al. (2013) Combining modality specific deep neural networks for emotion recognition in video. In: Proceedings of the 15th ACM on International Conference on Multimodal Interaction ACM, pp 543\u2013550","DOI":"10.1145\/2522848.2531745"},{"key":"1024_CR7","doi-asserted-by":"crossref","unstructured":"Levi G, Hassner T (2015) Emotion recognition in the wild via convolutional neural networks and mapped binary patterns. In: Proceedings of the 2015 ACM on International Conference on Multimodal Interaction ACM, pp 503\u2013510","DOI":"10.1145\/2818346.2830587"},{"key":"1024_CR8","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1016\/j.neucom.2017.08.043","volume":"273","author":"N Zeng","year":"2018","unstructured":"Zeng N, Zhang H, Song B, Liu W, Li Y, Dobaie AM (2018) Facial expression recognition via learning deep sparse autoencoders. Neurocomputing 273:643\u2013649","journal-title":"Neurocomputing"},{"key":"1024_CR9","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, pp 1097\u20131105"},{"key":"1024_CR10","unstructured":"Simonyan, K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556"},{"key":"1024_CR11","doi-asserted-by":"crossref","unstructured":"Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V, Rabinovich A (2015) Going deeper with convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 1\u20139","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"1024_CR12","doi-asserted-by":"crossref","unstructured":"Bazrafkan S, Nedelcu T, Filipczuk P, Corcoran P (2017) Deep learning for facial expression recognition: a step closer to a smartphone that knows your moods. In: 2017 IEEE International Conference on Consumer Electronics (ICCE), pp 217\u2013220","DOI":"10.1109\/ICCE.2017.7889290"},{"key":"1024_CR13","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.imavis.2017.01.012","volume":"65","author":"H Kaya","year":"2017","unstructured":"Kaya H, G\u00fcrp\u0131nar F, Salah AA (2017) Video-based emotion recognition in the wild using deep transfer learning and score fusion. Image Vision Comput 65:66\u201375","journal-title":"Image Vision Comput"},{"key":"1024_CR14","unstructured":"Knyazev B, Shvetsov R, Efremova N, Kuharenko A (2017) Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video. arXiv preprint arXiv:1711.04598"},{"key":"1024_CR15","doi-asserted-by":"crossref","unstructured":"Ding H, Zhou SK, Chellappa R (2017) Facenet2expnet: Regularizing a deep face recognition net for expression recognition. In: 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), pp 118\u2013126","DOI":"10.1109\/FG.2017.23"},{"key":"1024_CR16","unstructured":"Salimans T, Goodfellow I, Zaremba W, Cheung V, Radford A, Chen X (2016) Improved techniques for training gans. In: Advances in neural information processing systems, pp 2234\u20132242"},{"key":"1024_CR17","unstructured":"Radford A, Metz L, Chintala S (2015) Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434"},{"key":"1024_CR18","doi-asserted-by":"crossref","unstructured":"Chang X, Nie F, Yang Y, Huang H (2014) A convex formulation for semi-supervised multi-label feature selection. In: AAAI, pp 1171\u20131177","DOI":"10.1609\/aaai.v28i1.8922"},{"issue":"5","key":"1024_CR19","doi-asserted-by":"publisher","first-page":"2545","DOI":"10.1109\/TIP.2017.2675341","volume":"26","author":"Y Gao","year":"2017","unstructured":"Gao Y, Ma J, Yuille AL (2017) Semi-supervised sparse representation based classification for face recognition with insufficient labeled samples. IEEE Trans Image Process 26(5):2545\u20132560","journal-title":"IEEE Trans Image Process"},{"key":"1024_CR20","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. In: Advances in neural information processing systems, pp 2672\u20132680"},{"key":"1024_CR21","unstructured":"Lee DH (2013) Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks. In: Workshop on Challenges in Representation Learning, ICML, vol. 3, p 2"},{"key":"1024_CR22","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.neunet.2018.02.002","volume":"102","author":"J Wen","year":"2018","unstructured":"Wen J, Xu Y, Li Z, Ma Z, Xu Y (2018) Inter-class sparsity based discriminative least square regression. Neural Netw 102:36\u201347","journal-title":"Neural Netw"},{"issue":"2","key":"1024_CR23","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1109\/TCSVT.2018.2799214","volume":"29","author":"J Wen","year":"2018","unstructured":"Wen J, Fang X, Cui J, Fei L, Yan K, Chen Y, Xu Y (2018) Robust sparse linear discriminant analysis. IEEE Trans Circuits Syst Video Technol 29(2):390\u2013403","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"1","key":"1024_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10919-010-0095-9","volume":"35","author":"EB Roesch","year":"2011","unstructured":"Roesch EB, Tamarit L, Reveret L, Grandjean D, Sander D, Scherer KR (2011) Facsgen: a tool to synthesize emotional facial expressions through systematic manipulation of facial action units. J Nonverbal Behav 35(1):1\u201316","journal-title":"J Nonverbal Behav"},{"key":"1024_CR25","volume-title":"What the face reveals: basic and applied studies of spontaneous expression using the Facial Action Coding System (FACS)","author":"P Ekman","year":"1997","unstructured":"Ekman P, Rosenberg EL (1997) What the face reveals: basic and applied studies of spontaneous expression using the Facial Action Coding System (FACS). Oxford University Press, Oxford"},{"key":"1024_CR26","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.procs.2017.03.069","volume":"107","author":"J Li","year":"2017","unstructured":"Li J, Zhang D, Zhang J, Zhang J, Li T, Xia Y, Yan Q, Xun L (2017) Facial expression recognition with faster R-CNN. Procedia Comput Sci 107:135\u2013140","journal-title":"Procedia Comput Sci"},{"key":"1024_CR27","unstructured":"Ren S, He K, Girshick R, Sun J (2015) Faster r-cnn: Towards real-time object detection with region proposal networks. In: Advances in neural information processing systems, pp 91\u201399"},{"key":"1024_CR28","doi-asserted-by":"crossref","unstructured":"Hu P, Cai D, Wang S, Yao A, Chen Y (2017) Learning supervised scoring ensemble for emotion recognition in the wild. In: Proceedings of the 19th ACM International Conference on Multimodal Interaction, pp 553\u2013560","DOI":"10.1145\/3136755.3143009"},{"issue":"1","key":"1024_CR29","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1109\/TPAMI.2012.59","volume":"35","author":"S Ji","year":"2013","unstructured":"Ji S, Xu W, Yang M, Yu K (2013) 3D convolutional neural networks for human action recognition. IEEE Trans Pattern Anal Mach Intell 35(1):221\u2013231","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1024_CR30","doi-asserted-by":"crossref","unstructured":"Tran D, Bourdev L, Fergus R, Torresani L, Paluri M (2015) Learning spatiotemporal features with 3d convolutional networks. In: Proceedings of the IEEE international conference on computer vision, pp 4489\u20134497","DOI":"10.1109\/ICCV.2015.510"},{"key":"1024_CR31","unstructured":"Pons G, Masip D (2018) Multi-task, multi-label and multi-domain learning with residual convolutional networks for emotion recognition. arXiv preprint arXiv:1802.06664"},{"key":"1024_CR32","doi-asserted-by":"crossref","unstructured":"Cohen I, Sebe N, Cozman FG, Huang TS (2003) Semi-supervised learning for facial expression recognition. In: Proceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, pp 17\u201322","DOI":"10.1145\/973264.973268"},{"key":"1024_CR33","doi-asserted-by":"crossref","unstructured":"Zhang Z, Ringeval F, Dong B, Coutinho E, Marchi E, Sch\u00fcller B (2016) Enhanced semi-supervised learning for multimodal emotion recognition. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 5185\u20135189","DOI":"10.1109\/ICASSP.2016.7472666"},{"key":"1024_CR34","unstructured":"Du C, Du C, Li J, Zheng Wl, Lu Bl, He H (2017) Semi-supervised bayesian deep multi-modal emotion recognition. arXiv preprint arXiv:1704.07548"},{"key":"1024_CR35","doi-asserted-by":"crossref","unstructured":"Haeusser P, Mordvintsev A, Cremers D (2017) Learning by association\u2013a versatile semi-supervised training method for neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 89\u201398","DOI":"10.1109\/CVPR.2017.74"},{"key":"1024_CR36","doi-asserted-by":"crossref","unstructured":"Haeusser P, Frerix T, Mordvintsev A, Cremers D (2017) Associative domain adaptation. In: Proceedings of the IEEE Conference on International Conference on Computer Vision (ICCV), pp 2765\u20132773","DOI":"10.1109\/ICCV.2017.301"},{"key":"1024_CR37","doi-asserted-by":"crossref","unstructured":"Cai J, Meng Z, Khan AS, Li Z, O\u2019Reilly J, Tong Y (2018) Island loss for learning discriminative features in facial expression recognition. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition, pp 302\u2013309","DOI":"10.1109\/FG.2018.00051"},{"issue":"8","key":"1024_CR38","doi-asserted-by":"publisher","first-page":"1377","DOI":"10.1080\/02699930903485076","volume":"24","author":"O Langner","year":"2010","unstructured":"Langner O, Dotsch R, Bijlstra G, Wigboldus DH, Hawk ST, Van Knippenberg A (2010) Presentation and validation of the radboud faces database. Cognit Emotion 24(8):1377\u20131388","journal-title":"Cognit Emotion"},{"issue":"9","key":"1024_CR39","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1016\/j.imavis.2011.07.002","volume":"29","author":"G Zhao","year":"2011","unstructured":"Zhao G, Huang X, Taini M, Li SZ, Pietik\u00e4Inen M (2011) Facial expression recognition from near-infrared videos. Image Vis Comput 29(9):607\u2013619","journal-title":"Image Vis Comput"},{"key":"1024_CR40","unstructured":"Krinidis S, Pitas I (2006) Facial expression synthesis through facial expressions statistical analysis. In: 2006 14th European Signal Processing Conference, pp 1\u20135"},{"key":"1024_CR41","doi-asserted-by":"crossref","unstructured":"Abbasnejad I, Sridharan S, Nguyen D, Denman S, Fookes C, Lucey S (2017) Using synthetic data to improve facial expression analysis with 3d convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 1609\u20131618","DOI":"10.1109\/ICCVW.2017.189"},{"key":"1024_CR42","doi-asserted-by":"crossref","unstructured":"Zhou Y, Shi BE (2017) Photorealistic facial expression synthesis by the conditional difference adversarial autoencoder. In: 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), pp 370\u2013376","DOI":"10.1109\/ACII.2017.8273626"},{"key":"1024_CR43","unstructured":"Kulkarni TD, Whitney WF, Kohli P, Tenenbaum J (2015) Deep convolutional inverse graphics network. In: Advances in Neural information processing systems, pp 2539\u20132547"},{"key":"1024_CR44","doi-asserted-by":"crossref","unstructured":"Dosovitskiy A, Tobias\u00a0Springenberg J, Brox T (2015) Learning to generate chairs with convolutional neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 1538\u20131546","DOI":"10.1109\/CVPR.2015.7298761"},{"issue":"Jul","key":"1024_CR45","first-page":"1755","volume":"10","author":"DE King","year":"2009","unstructured":"King DE (2009) Dlib-ml: a machine learning toolkit. J Mach Learn Res 10(Jul):1755\u20131758","journal-title":"J Mach Learn Res"},{"key":"1024_CR46","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.imavis.2016.01.002","volume":"47","author":"C Sagonas","year":"2016","unstructured":"Sagonas C, Antonakos E, Tzimiropoulos G, Zafeiriou S, Pantic M (2016) 300 faces in-the-wild challenge: database and results. Image Vis Comput 47:3\u201318","journal-title":"Image Vis Comput"},{"issue":"3","key":"1024_CR47","doi-asserted-by":"publisher","first-page":"1481","DOI":"10.1007\/s11042-014-2004-4","volume":"75","author":"W Liu","year":"2016","unstructured":"Liu W, Zhang H, Tao D, Wang Y, Lu K (2016) Large-scale paralleled sparse principal component analysis. Multimedia Tools Appl 75(3):1481\u20131493","journal-title":"Multimedia Tools Appl"},{"key":"1024_CR48","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1016\/j.neucom.2017.06.050","volume":"267","author":"W Sun","year":"2017","unstructured":"Sun W, Zhao H, Jin Z (2017) An efficient unconstrained facial expression recognition algorithm based on stack binarized auto-encoders and binarized neural networks. Neurocomputing 267:385\u2013395","journal-title":"Neurocomputing"},{"key":"1024_CR49","doi-asserted-by":"crossref","unstructured":"Moeini A, Moeini H (2015) Multimodal facial expression recognition based on 3D face reconstruction from 2D images. In: Face and facial expression recognition from real world videos, Springer, pp 46\u201357","DOI":"10.1007\/978-3-319-13737-7_5"},{"key":"1024_CR50","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.neucom.2018.03.034","volume":"296","author":"W Sun","year":"2018","unstructured":"Sun W, Zhao H, Jin Z (2018) A visual attention based roi detection method for facial expression recognition. Neurocomputing 296:12\u201322","journal-title":"Neurocomputing"},{"key":"1024_CR51","doi-asserted-by":"crossref","unstructured":"Scovanner P, Ali S, Shah M (2007) A 3-dimensional sift descriptor and its application to action recognition. In: Proceedings of the 15th ACM international conference on Multimedia, pp 357\u2013360","DOI":"10.1145\/1291233.1291311"},{"key":"1024_CR52","unstructured":"Cugu I, Sener E, AkbaS E (2017) Microexpnet: An extremely small and fast model for expression recognition from frontal face images. arXiv preprint arXiv:1711.07011"},{"key":"1024_CR53","doi-asserted-by":"crossref","unstructured":"Klaser A, Marsza\u0142ek M, Schmid C (2008) A spatio-temporal descriptor based on 3d-gradients. In: BMVC 2008-19th British Machine Vision Conference. British Machine Vision Association, p 275-1","DOI":"10.5244\/C.22.99"},{"key":"1024_CR54","doi-asserted-by":"crossref","unstructured":"Jung H, Lee S, Yim J, Park S, Kim J (2015) Joint fine-tuning in deep neural networks for facial expression recognition. In: Proceedings of the IEEE international conference on computer vision, pp 2983\u20132991","DOI":"10.1109\/ICCV.2015.341"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-01024-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-019-01024-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-01024-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T00:27:14Z","timestamp":1695342434000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-019-01024-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,23]]},"references-count":54,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,4]]}},"alternative-id":["1024"],"URL":"https:\/\/doi.org\/10.1007\/s13042-019-01024-2","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,23]]},"assertion":[{"value":"18 March 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 October 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 October 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}