Frontalization and adaptive exponential ensemble rule for deep-learning-based facial expression recognition system
作者：
Highlights：
• An advanced CNN based facial expression recognition (FER) method is proposed.
• Its accuracy is higher than that of other stated-of-the-art CNN-based methods.
• Advanced frontalization method is used to make the input of the CNN more meaningful.
• A hierarchical AEWEA system is applied to integrate the advantages of each model.
• The shortcut CNN, which considers block relations and is easier to train, is adopted.
摘要
•An advanced CNN based facial expression recognition (FER) method is proposed.•Its accuracy is higher than that of other stated-of-the-art CNN-based methods.•Advanced frontalization method is used to make the input of the CNN more meaningful.•A hierarchical AEWEA system is applied to integrate the advantages of each model.•The shortcut CNN, which considers block relations and is easier to train, is adopted.
论文关键词：Facial expression,Face recognition,Convolutional neural network,Computer vision,Face frontalization,Hierarchical structure
论文评审过程：Received 21 February 2020, Revised 5 April 2021, Accepted 7 May 2021, Available online 13 May 2021, Version of Record 15 May 2021.
论文官网地址：https://doi.org/10.1016/j.image.2021.116321
