Dispersion Constraint Based Non-negative Sparse Coding Model

被引：0
|
作者：
Xin Wang
Can Wang
Li Shang
Zhan-Li Sun
机构：
[1] Zhejiang University,Zhejiang Provincial Key Laboratory of Service Robot, College of Computer Science
[2] Simon Fraser University,Department of Communication Technology, College of Electronic Information Engineering
[3] Suzhou Vocational University,School of Electrical Engineering and Automation
[4] Anhui University,undefined
来源：
Neural Processing Letters | 2016年 / 43卷
关键词：
Classification constraint; Non-negative sparse coding (NNSC); Dispersion ratio; Classifiers; Within-class; Between-class;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Based on advantages of basic non-negative sparse coding (NNSC) model, and considered the prior class constraint of image features, a novel NNSC model is discussed here. In this NNSC model, the sparseness criteria is selected as a two-parameter density estimation model and the dispersion ratio of within-class and between-class is used as the class constraint. Utilizing this NNSC model, image features can be extracted successfully. Further, the feature recognition task by using different classifiers can be implemented well. Simulation results prove that our NNSC model proposed is indeed effective in extracting image features and recognition task in application.
引用
收藏
页码：603 / 609
页数：6
相关论文
共 50 条
  • [21] Face recognition using localized features based on non-negative sparse coding
    Bhavin J. Shastri
    Martin D. Levine
    Machine Vision and Applications, 2007, 18 : 107 - 122
  • [22] Face recognition using localized features based on non-negative sparse coding
    Shastri, Bhavin J.
    Levine, Martin D.
    MACHINE VISION AND APPLICATIONS, 2007, 18 (02) : 107 - 122
  • [23] Multi-constraint non-negative matrix factorization for community detection: orthogonal regular sparse constraint non-negative matrix factorization
    Chen, Zigang
    Xiao, Qi
    Leng, Tao
    Zhang, Zhenjiang
    Pan, Ding
    Liu, Yuhong
    Li, Xiaoyong
    COMPLEX & INTELLIGENT SYSTEMS, 2024, 10 (04) : 4697 - 4712
  • [24] Non-negative Kernel Sparse Coding for the Analysis of Motion Data
    Hosseini, Babak
    Huelsmann, Felix
    Botsch, Mario
    Hammer, Barbara
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2016, PT II, 2016, 9887 : 506 - 514
  • [25] Online Pattern Learning for Non-Negative Convolutive Sparse Coding
    Wang, Dong
    Vipperla, Ravichander
    Evans, Nicholas
    12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5, 2011, : 72 - 75
  • [26] SAR ATR based on HRRP time-frequency non-negative sparse coding
    Zhang, Xin-Zheng
    Liu, Shu-Jun
    Qin, Jian-Hong
    Huang, Pei-Kang
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2014, 36 (10): : 1934 - 1941
  • [27] Non-Negative Sparse Coding based Scalable Access Control using Fingertip ECG
    Raj, Peter Sam
    Sonowal, Sukanya
    Hatzinakos, Dimitrios
    2014 IEEE/IAPR INTERNATIONAL JOINT CONFERENCE ON BIOMETRICS (IJCB 2014), 2014,
  • [28] Medical image classification based on multi-scale non-negative sparse coding
    Zhang, Ruijie
    Shen, Jian
    Wei, Fushan
    Li, Xiong
    Sangaiah, Arun Kumar
    ARTIFICIAL INTELLIGENCE IN MEDICINE, 2017, 83 : 44 - 51
  • [29] Image Classification by Non-Negative Sparse Coding, Low-Rank and Sparse Decomposition
    Zhang, Chunjie
    Liu, Jing
    Tian, Qi
    Xu, Changsheng
    Lu, Hanqing
    Ma, Songde
    2011 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2011, : 1673 - 1680
  • [30] VOICE ACTIVITY DETECTION USING CONVOLUTIVE NON-NEGATIVE SPARSE CODING
    Teng, Peng
    Jia, Yunde
    2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2013, : 7373 - 7377
12345