A Joint Convolutional Bidirectional LSTM Framework for Facial Expression Recognition-Reference-Cited by-同舟云学术

A Joint Convolutional Bidirectional LSTM Framework for Facial Expression Recognition

Published:2018 Issue:4 Volume:E101.D Page:1217-1220
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

YAN Jingwei¹,ZHENG Wenming¹,CUI Zhen²,SONG Peng³

Affiliation:

1. Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science and Medical Engineering, Southeast University

2. School of Computer Science and Engineering, Nanjing University of Science and Technology

3. School of Computer and Control Engineering, Yantai University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E101.D/4/E101.D_2017EDL8208/_pdf

Reference16 articles.

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2. [2] W. Zheng, “Multi-view facial expression recognition based on group sparse reduced-rank regression,” IEEE Transactions on Affective Computing, vol.5, no.1, pp.71-85, 2014. 10.1109/taffc.2014.2304712

3. [3] G. Lyu, H. Yin, X. Yu, and S. Luo, “A local characteristic image restoration based on convolutional neural network,” IEICE Trans. Inf. & Syst., vol.E99-D, no.8, pp.2190-2193, 2016. 10.1587/transinf.2016edl8021

4. [4] W. Han, X. Zhang, M. Sun, L. Li, and W. Shi, “An improved supervised speech separation method based on perceptual weighted deep recurrent neural networks,” IEICE Trans. Fundamentals, vol.E100-A, no.2, pp.718-721, 2017. 10.1587/transfun.e100.a.718

5. [5] T. Zhang, W. Zheng, Z. Cui, Y. Zong, J. Yan, and K. Yan, “A deep neural network-driven feature learning method for multi-view facial expression recognition,” IEEE Trans. Multimedia, vol.18, no.12, pp.2528-2536, 2016. 10.1109/tmm.2016.2598092

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