[1] [1] YU J, GAO H, JU Z J, et al. Deep object detector with attentional spatiotemporal LSTM for space human-robot interaction[J]. IEEE transactions on human-machine systems, 2022, 52: 784-793.

[2] [2] YU J, GAO H, JU Z J, et al. Deep temporal model-based identity aware hand detection for space human-robot interaction[J]. IEEE transactions on cybernetics, 2021, 52: 13738-13751.

[3] [3] XU L, ZHAO S, WANG T. Aero-optic imaging deviation prediction based on ISSA-ELM[J]. Optoelectronics letters, 2023, 19(7): 425-431.

[4] [4] FANG Y, ZHOU D, LI K, et al. Attribute-driven granular model for EMG-based pinch and fingertip force grand recognition[J]. IEEE transactions on cybernetics,2019, 51(2): 789-800.

[5] [5] LI K, BOYD P, JU Z J, et al. Electrotactile feedback in a virtual hand rehabilitation platform: evaluation and implementation[J]. IEEE transactions on automation science and engineering, 2018, 16(4): 1556-1565.

[6] [6] LI S, DENG W. Reliable crowd sourcing and deep locality-preserving learning for unconstrained facial expression recognition[J]. IEEE transactions on image processing, 2018, 28: 356-370.

[7] [7] GOODFELLOW I J, ERHAN D, CARRIER P L, et al. Challenges in representation learning: a report on three machine learning contests[J]. Proceedings of the international conference on neural information processing,2013: 117-124.

[8] [8] ZENG D, LIN Z, YAN X. Face2exp: combating data biases for facial expression recognition[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-24, 2022, New Orleans, LA, USA. New York: IEEE, 2022: 20291-20300.

[9] [9] WANG K, PENG X, YANG J, et al. Region attention networks for pose and occlusion robust facial expression recognition[J]. IEEE transactions on image processing,2020, 29: 4057- 4069.

[10] [10] LIU J, JI X, WANG M. SFR-Net: sample-aware and feature refinement network for cross-domain micro-expression recognition[J]. Optoelectronics letters,2023, 19(7): 437-442.

[11] [11] CHEN L, WANG K, LI M, et al. K-means clustering-based kernel canonical correlation analysis for multimodal emotion recognition in human-robot interaction[J]. IEEE transactions on industrial electronics,2022, 70(1): 1016-1024.

[12] [12] ZENG J, SHAN S, CHEN X. Facial expression recognition with inconsistently annotated datasets[C]//Proceedings of the European Conference on Computer Vision (ECCV), September 8-14, 2018, Munich, Germany. Heidelberg: Springer, 2018: 222-237.

[13] [13] FAN Y, LAM J C, LI V O. Multi-region ensemble convolutional neural network for facial expression recognition[J]. Proceedings of the international conference on artificial neural networks, 2018: 84-94.

[14] [14] LI Y, ZENG J, SHAN S, et al. Occlusion aware facial expression recognition using CNN with attention mechanism[J]. IEEE transactions on image processing,2018, 28: 2439-2450.

[15] [15] SHI J, ZHU S. Learning to amend facial expression representation via de-albino and affinity[EB/OL]. (2021-03-18) [2023-10-23]. https://arxiv.org/abs/2103.10189.

[16] [16] LI S, DENG W, DU J. Reliable crowdsourcing and deep locality-preserving learning for expression recognition in the wild[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017:2852-2861.