Virtual facial expression recognition using deep CNN with ensemble learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-020-02866-3.pdf
Reference58 articles.
1. Kim J, Kim B, Roy PP, Jeong D (2019) Efficient facial expression recognition algorithm based on hierarchical deep neural network structure. In: IEEE Access 7:41273–41285.
2. Mandal M, Verma M, Mathur S, Vipparthi S, Murala S, Deveerasetty K (2019) Radap: regional adaptive affinitive patterns with logical operators for facial expression recognition. IET Image Process 13:850–861
3. Bartlett MS, Littlewort G, Fasel I, Movellan JR (2003) Real time face detection and facial expression recognition: Development and applications to human computer interaction. Proc IEEE Conf Comput Vis Pattern Recog Workshop 5:53–53.
4. Teow MYW (2017) Understanding convolutional neural networks using a minimal model for handwritten digit recognition(2017). In: 2017 IEEE 2nd international conference on automatic control and intelligent systems (I2CACIS), Kota Kinabalu, pp 167–172.
5. Lyons M, Akamatsu S, Kamachi M, Gyoba J (1998) Coding facial expressions with Gabor wavelets. In: Proceeding - 3rd IEEE Int Conf Autom Face Gesture Recognition, FG 1998, pp 200–205
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