Softmax regression based deep sparse autoencoder network for facial emotion recognition in human-robot interaction-Reference-Cited by-同舟云学术

Softmax regression based deep sparse autoencoder network for facial emotion recognition in human-robot interaction

Published:2018-02 Issue: Volume:428 Page:49-61
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Chen Luefeng,Zhou Mengtian,Su Wanjuan,Wu Min,She Jinhua,Hirota Kaoru

Funder

National Natural Science Foundation of China

Hubei Provincial Natural Science Foundation of China

China University of Geosciences

Wuhan Science and Technology

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference45 articles.

1. Towards an intelligent system for generating an adapted verbal and nonverbal combined behavior in human crobot interaction;Aly;Auton. Robots,2016

2. Adaptive appearance model tracking for still-to-video face recognition;Dewana;Pattern Recognit.,2016

3. Face recognition using kernel ridge regression;An,2007

4. Emotion-age-gender-nationality based intention understanding in human-robot interaction using two-layer fuzzy support vector regression;Chen;Int. J. Soc. Robot,2015

5. Adapting multi-robot behavior to communication atmosphere in humans-robots interaction using fuzzy production rule based friend-q learning;Chen;J. Adv. Comput. Intell. Intell. Inform.,2013

Cited by 162 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dual-STI: Dual-path spatial-temporal interaction learning for dynamic facial expression recognition;Information Sciences;2024-09

2. Towards the adversarial robustness of facial expression recognition: Facial attention-aware adversarial training;Neurocomputing;2024-06

3. A novel relation‐aware global attention network for sentiment analysis of students in the wisdom classroom;Concurrency and Computation: Practice and Experience;2024-05-13

4. Automated Facial Expression Detection using Genetic Algorithm optimization with Fuzzy C-means Clustering Algorithm;2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE);2024-04-26

5. Emotional Recognition Based on Faces through Deep Learning Algorithms;International Journal of Innovative Science and Research Technology (IJISRT);2024-04-03