Emotion Recognition Model Based on RBF Neural Network in E-Learning

被引：1
|
作者：
Wang, Wansen [1 ]
Li, Rui [1 ]
机构：
[1] Capital Normal Univ, Coll Informat Engn, Beijing, Peoples R China
来源：
FOUNDATIONS OF INTELLIGENT SYSTEMS (ISKE 2013) | 2014年 / 277卷
关键词：
E-Learning; RBF neural network; Emotion recognition model;
D O I：
10.1007/978-3-642-54924-3_54
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a method that uses RBF neural network to build Emotion Recognition Model in E-Learning system. It can effectively identify academic emotion, and is aimed at improving the teaching achievements and making up the lack of emotion in the traditional teaching mode. The experiments compare the emotion recognition rate of the BP neural network and RBF neural network; the recognition rate of RBF neural network is higher than BP neural network. The results show that the Emotion Recognition Model based on RBF neural network has high rate of recognition and better real-time capabilities.
引用
收藏
页码：567 / 576
页数：10
相关论文
共 50 条
  • [41] Deep Neural Network for Emotion Recognition Based on Meta-Transfer Learning
    Tang, Hengyao
    Jiang, Guosong
    Wang, Qingdong
    [J]. IEEE ACCESS, 2022, 10 : 78114 - 78122
  • [42] RESEARCH OF IMPROVED SVM MODEL BASED ON GA IN E-LEARNING EMOTION CLASSIFICATION
    Wang, Wansen
    Ding, Wenlan
    [J]. 2012 IEEE 2ND INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTELLIGENT SYSTEMS (CCIS) VOLS 1-3, 2012, : 919 - 923
  • [43] A predictive model based on RBF Neural Network
    Song, YB
    Wang, PJ
    [J]. PROCEEDINGS OF THE SIXTH IASTED INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND CONTROL, 2004, : 380 - 383
  • [44] Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
    Landowska, Agnieszka
    Brodny, Grzegorz
    Wrobel, Michal R.
    [J]. PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED EDUCATION (CSEDU), VOL 2, 2017, : 383 - 389
  • [45] Artificial emotion model based on reinforcement learning mechanism of neural network
    SHI Xue-fei1
    [J]. The Journal of China Universities of Posts and Telecommunications, 2011, 18 (03) : 105 - 109
  • [46] Student Emotion Recognition System (SERS) for e-learning improvement based on learner concentration metric
    Krithika, L. B.
    Priya, Lakshmi G. G.
    [J]. INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELLING AND SECURITY (CMS 2016), 2016, 85 : 767 - 776
  • [47] Question classification for E-learning by artificial neural network
    Fei, T
    Heng, WJ
    Toh, KC
    Qi, T
    [J]. ICICS-PCM 2003, VOLS 1-3, PROCEEDINGS, 2003, : 1757 - 1761
  • [48] A RBF Neural Network Learning Algorithm Based on NCPSO
    Xue Lei
    Sun Changyin
    Mu Chaoxu
    Huang Yiqing
    [J]. 2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 3294 - 3299
  • [49] A Recognition Method of Surface -Water Based on RBF Neural Network
    Chen Xue-lian
    Hu Jing-tao
    [J]. 2013 IEEE 4TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION (ICEIEC), 2014, : 217 - 221
  • [50] RBF Neural Network Based on Dynamic Clustering for Face Recognition
    Di, Xiao
    Jin-guo, Lin
    [J]. 2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 4081 - 4085
12345