The following publications are possibly variants of this publication:
- Lightweight Deep Learning Model For Facial Expression RecognitionLaha Ale, Xiaojie Fang, Dajiang Chen, Ye Wang, Ning Zhang 0007. trustcom 2019: 707-712 [doi]
- Sample awareness-based personalized facial expression recognitionHuihui Li, Guihua Wen. apin, 49(8):2956-2969, 2019. [doi]
- Facial expression recognition sensing the complexity of testing samplesTian-Yuan Chang, Huihui Li, Guihua Wen, Yang Hu, Jiajiong Ma. apin, 49(12):4319-4334, 2019. [doi]
- Lightweight Facial Expression Recognition Network with Dynamic Deep Mutual LearningMinchen Zeng, Yutong Luo, Guangyuan Liu. huc 2023: 222-226 [doi]
- A lightweight facial expression recognition model for automated engagement detectionZibin Zhao, Yinbei Li, Jiaqiang Yang, Yuliang Ma. sivp, 18(4):3553-3563, June 2024. [doi]
- Facial expression recognition based on multi-channel fusion and lightweight neural networkYali Yu, Hua Huo, Junqiang Liu. soco, 27(24):18549-18563, December 2023. [doi]
- Robust Lightweight Facial Expression Recognition Network with Label Distribution TrainingZengqun Zhao, Qingshan Liu, Feng Zhou. AAAI 2021: 3510-3519 [doi]
- Lightweight Deep Convolutional Neural Networks for Facial Expression RecognitionYanan Wang, Jianming Wu, Keiichiro Hoashi. mmsp 2019: 1-6 [doi]
- A high-performance and lightweight framework for real-time facial expression recognitionXuebin Xu, ChenGuang Liu, Shuxin Cao, Longbin Lu. iet-ipr, 17(12):3500-3509, 2023. [doi]