Hassan M M, Alam M G R, Uddin M Z, et al. Human emotion recognition using deep belief network architecture[J]. Information Fusion, 2019, 51: 10-18.[2] H o s s a i n M S , M u h a m m a d G . E m o t i o n recognition using deep learning approach from audio–visual emotional big data[J]. Information Fusion, 2019, 49: 69-78.[3] Krizhevsky A, Sutskever I, Hinton G E, Imagenet classification with deep convolutional neural networks[C]//Advances in neural information processing systems.2012: 1097-1105.[4] Szegedy C, Liu W, Jia Y, et al. Going deeper with convolutions[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2015: 1–9.[5] Mollahosseini A, Hasani B, Salvador M J, et al. Facial expression recognition from world wild web[C]//Proceedings of the IEEE conference on computer vision and pattern recognition workshops. 2016: 58-65.[6] H i n t o n G E , S a b o u r S , F r o s s t N . Matrix capsules with EM rounting[C]//International conference on learning representations. 2018.[7] Barsoum E, Zhang C, Ferrer C C, et al. Training deep networks for facial expression recognition with crowd-sourced label distribution[C]//Proceedings of the 18th ACM international conference on multimodal interaction. 2016: 279-83.[8] Kingma D P, Ba J. Adam: a method for stochastic optimization[J]. arXiv preprint arXiv: 1412.6980, 2014