Graph-based dynamic ensemble pruning for facial expression recognition-Reference-Cited by-同舟云学术

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Graph-based dynamic ensemble pruning for facial expression recognition

Published:2019-03-16 Issue:9 Volume:49 Page:3188-3206
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Li Danyang,Wen Guihua^ORCID,Li Xu,Cai Xianfa

Funder

The PhD Start-up Fund of Natural Science Foundation of Guangdong Province

the Research Projects of Introducing Talents in Guizhou University

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

http://link.springer.com/content/pdf/10.1007/s10489-019-01435-2.pdf

Reference60 articles.

1. Ekman P, Friesen WV (1971) Constants across cultures in the face and emotion. Pers Soc Psychol 17 (2):124–129

2. Liu, Yuan XH, Gong X, Xie Z, Fang F, Luo ZW (2018) Conditional convolution neural network enhanced random forest for facial expression recognition. Pattern Recogn 84:251–261

3. Yaddaden Y, Adda M, Bouzouane A, Gaboury S, Bouchard B (2018) User action and facial expression recognition for error detection system in an ambient assisted environment. Expert Syst Appl 112:173–189. https://doi.org/10.1016/j.eswa.2018.06.033

4. Yu ZB, Liu GC, Liu QS, Deng JK (2018) Spatio-temporal convolutional features with nested LSTM for facial expression recognition. Neurocomputing 317:50–57. https://doi.org/10.1016/j.neucom.2018.07.028

5. Sun Z, Chiong R, Hu ZP (2018) An extended dictionary representation approach with deep subspace learning for facial expression recognition. Neurocomputing 316:1–9. https://doi.org/10.1016/j.neucom.2018.07.045

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