Haiyan Ye, and Qilin Wu


  1. [1] R. Zhi, J. Wan, D. Zhang, and W. Li, Correlation betweenhedonic liking and facial expression measurement usingdynamic affective response representation, Food ResearchInternational, 108(1), 2018, 237–245.
  2. [2] Z. Xi, Y. Niu, J. Chen, X. Kan, and H. Liu, Facial expressionrecognition of industrial Internet of Things by parallel neuralnetworks combining texture features, IEEE Transactions onIndustrial Informatics, 17(4), 2020, 2784–2793.
  3. [3] Z. Zhou, J. Fu, J. Lv, and Q. Zhang, An improvedcomplementary filter algorithm in the application of the mobilerobot attitude estimation, Control and Intelligent Systems,46(4), 2018, 163–169.
  4. [4] L.-M. Li, J. Zhao, and C.-J. Yan, Robot-to-human handoverin a comfortable and friendly manner, Control and IntelligentSystems, 46(4), 2018, 187–195.
  5. [5] S. Li, and W. Deng, Blended emotion in-the-wild: Multi-labelfacial expression recognition using crowdsourced annotationsand deep locality feature learning, International Journal ofComputer Vision, 127(6/7), 2019, 884–906.
  6. [6] R. V. Priya, V. Vijayakumar, and J. Tavares, MQSMER: Amixed quadratic shape model with optimal fuzzy membershipfunctions for emotion recognition, Neural Computing andApplications, 32(8), 2020, 3165–3182.
  7. [7] N. Yitzhak, T. Gurevich, N. Inbar, M. Lecker, D. Atias, H.Avramovich, and H. Aviezer, Recognition of emotion fromsubtle and non-stereotypical dynamic facial expressions inHuntington’s disease, Cortex, 126, 2020, 343–354.
  8. [8] Y. Liang, B. Liu, H. Ji, and X. Li, Network representationsof facial and bodily expressions: Evidence from multivariateconnectivity pattern classification, Frontiers in Neuroscience13, 2019, 1111–1121.
  9. [9] H. L. Yitzhak, Y. T. Kelman, A. Moskovenko, E. Zhovnerchuk,and Z. Zalevsky, Emotion recognition using speckle patternanalysis and k-nearest neighbors classification, Journal ofOptics, 23(1), 2020, 015302.
  10. [10] W. Wei, Q. Jia, Y. Feng, G. Chen, and M. Chu,Multi-modal facial expression feature based on deep-neuralnetworks, Journal on Multimodal User Interfaces, 14(1), 2020,17–23.
  11. [11] E. Mansouri-Benssassi and J. Ye, Generalisation and robustnessinvestigation for facial and speech emotion recognition usingbio-inspired spiking neural networks, Soft Computing, 25(2),2021, 1717–1730.
  12. [12] D.K. Jain, P. Shamsolmoali, and P. Sehdev, Extendeddeep neural network for facial emotion recognition, PatternRecognition Letters, 120(1), 2019, 69–74.
  13. [13] E. Pei, M.C. Oveneke, Y. Zhao, D. Jiang, and H. Sahli,Monocular 3D facial expression features for continuous affectrecognition, IEEE Transactions on Multimedia, 23, 2020,3540–3550.
  14. [14] K. Chen, C. Wang, K. Wang, C. Yin, C. Zhao, T. Xu,X. Zhang, Z. Huang, M. Liu, and T. Yang, HEU emotion:A large-scale database for multimodal emotion recognition inthe wild, Neural Computing and Applications, 33(14), 2021,8669–8685.
  15. [15] W.J. Baddar, S. Lee, and Y.M. Ro, On-the-fly facial expres-sion prediction using LSTM encoded appearance-suppresseddynamics, IEEE Transactions on Affective Computing, 13(1),2022, 159–174.
  16. [16] A. Ullah, J. Wang, M.S. Anwar, U. Ahmad, U. Saeed, and Z. Fei,Facial expression recognition of nonlinear facial variationsusing deep locality de-expression residue learning in the wild,Electronics, 8(12), 2019, 1–16.
  17. [17] B. T. Shoba and I. Shatheesh Sam, Aging facial recognition forfeature extraction using adaptive fully recurrent deep neurallearning, The Computer Journal 65(7), 2022, 1923–1936.
  18. [18] T. Rao, J. Li, X. Wang, Y. Sun, and H. Chen, Facial expressionrecognition with multiscale graph convolutional networks, IEEEMultiMedia, 28(2), 2021, 11–19.
  19. [19] C. Niu and Y. Zhu, Design of unsupervised facial expressionanimation based on geometric grid measurement, InternationalJournal of Reasoning-based Intelligent Systems, 10(2), 2018,96–101.
  20. [20] A. Bhatt, T. Alam, K.P. Rane, R. Nandal, M. Malik, R. Neware,and S. Goel, Quantum-inspired meta-heuristic algorithms withdeep learning for facial expression recognition under varyingyaw angles, International Journal of Modern Physics C, 33(04),2022, 2250045.
  21. [21] G. Bargshady, X. Zhou, R.C. Deo, J. Soar, F. Whittaker,and H. Wang, Enhanced deep learning algorithm developmentto detect pain intensity from facial expression images, ExpertSystems with Applications, 149(1), 2020, 113–126.
  22. [22] Y. Liu, C. Feng, X. Yuan, L. Zhou, W. Wang, J. Qin, andZ. Luo, Clip-aware expressive feature learning for video-basedfacial expression recognition, Information Sciences, 598, 2022,182–195.
  23. [23] R. Zhi, X. Hu, C. Wang, and S. Liu, Development of a directmapping model between hedonic rating and facial responsesby dynamic facial expression representation, Food ResearchInternational, 137(6), 2020, 400–411.
  24. [24] F. Nan, W. Jing, F. Tian, J. Zhang, K. Chao, Z. Hong,and Q. Zheng, Feature super-resolution based facial expressionrecognition for multi-scale low-resolution images, Knowledge-Based Systems, 236, 2022, 107678.9
  25. [25] P. Liu, Y. Lin, Z. Meng, W. Deng, J.T. Zhou, and Y. Yang, Pointadversarial self-mining: A simple method for facial expressionrecognition, IEEE Transactions on Cybernetics, 52(12), 2021,12649–12660.
  26. [26] Y. Xu, Z. Hou, J. Liang, C. Chen, L. Jia, and Y. Song, Actionrecognition using weighted fusion of depth images and skeleton’skey frames, Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journalof Computer-Aided Design and Computer Graphics, 30(7),2018, 1313.
  27. [27] C. Pabba and P. Kumar, An intelligent system for monitoringstudents’ engagement in large classroom teaching through facialexpression recognition, Expert Systems, 39(1), 2022, e12839.
  28. [28] H. Xia, C. Li, Y. Tan, L. Li, and S. Song, Destruction andreconstruction learning for facial expression recognition, IEEEMultiMedia, 28(2), 2021, 20–28.
  29. [29] H. Yao, M. Yang, T. Chen, Y. Wei, and Y. Zhang, Depth-basedhuman activity recognition via multi-level fused features andfast broad learning system, International Journal of DistributedSensor Networks, 16(2), 2020, 155–168.
  30. [30] G. Lokku, G.H. Reddy, and M.N.G. Prasad, Optimized scale-invariant feature transform with local tri-directional patternsfor facial expression recognition with deep learning model, TheComputer Journal, 65(9), 2022, 2506–2527.
  31. [31] T. Liu, J. Wang, B. Yang, and X. Wang, Facial expressionrecognition method with multi-label distribution learning fornon-verbal behavior understanding in the classroom, InfraredPhysics & Technology, 112, 2021, 103594.
  32. [32] M. Gu, K. C. Li, Z. Li, Q. Han, and W. Fan, Recognitionof crop diseases based on depthwise separable convolution inedge computing, Sensors, 20(15), 2020, 1–16.
  33. [33] H. Li, N. Wang, X. Ding, X. Yang, and X. Gao, Adaptivelylearning facial expression representation via C-F labels anddistillation, IEEE Transactions on Image Processing, 30, 2021,2016–2028.
  34. [34] F. Cao, K. Zeng, W. Li, S. Liu, L. Zhang, S. Katembu, and Q.Xu, Influence of scene-based expectation on facial expressionperception: The moderating effect of cognitive load, BiologicalPsychology, 168, 2022, 108247.
  35. [35] T. Rao, J. Li, and X. Wang, Facial expression recognition withmultiscale graph convolutional networks, IEEE MultiMedia,28(2), 2021, 11–19.
  36. [36] Q. Zhong, B. Fang, S. Wei, Z. Wang, and H. Zhang,Facial expression recognition based on facial part attentionmechanism, Journal of Electronic Imaging, 30(3), 2021,031206–031206.
  37. [37] Y. Liu, W. Dai, F. Fang, Y. Chen, R. Huang, R. Wang,and B. Wan, Dynamic multi-channel metric network for jointpose-aware and identity-invariant facial expression recognition,Information Sciences, 578, 2021, 195–213.
  38. [38] L. Lu, Multi-angle face expression recognition based ongenerative adversarial networks, Computational Intelligence,38(1), 2022, 20–37.
  39. [39] X. Chen, L. Ke, Q. Du, J. Li, and X. Ding, Facial expressionrecognition using kernel entropy component analysis networkand DAGSVM, Complexity, 2021, 2021, 1–12.
  40. [40] Y. Wang, J. Wang, Y. Li, M. Yu, Y. Zhou, and B. Zhang, Facialexpression recognition with fused handcraft features based onpixel difference local directional number pattern, Journal ofIntelligent & Fuzzy Systems, 41(1), 2021, 113–123.
  41. [41] J. Han, L. Du, X. Ye, L. Zhang, and J. Feng, The devil isin the face: Exploiting harmonious representations for facialexpression recognition, Neurocomputing, 486, 2022, 104–113.
  42. [42] Y. Luo, J. Shao, and R. Yang, Collaborative attentiontransformer on facial expression recognition under partialocclusion, Journal of Electronic Imaging, 31(2), 2022,023037–023037.

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