Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 2
489-494,500

Discriminative dictionary learning based on locality intra-class structure

Chen Ziliua
Hu Gaopenga
Wang Xiaominga,b
Huang Zengxia
Du Yajuna
a. School of Computer & Software Engineer, b. Robotics Research Center, Xihua University, Chengdu 610039, China
DOI: 10.19734/j.issn.1001-3695.2019.11.0607

Abstract

Aiming at the limitation that the discriminative term of only embodies the max-margin principle as SVM, and fails to utilize the intrinsic structure information of data space, this paper proposed a novel discriminative dictionary learning method called discriminative dictionary learning based on locality intra-class structure(LCSDDL). The proposed method combined max-margin principle with local Fisher discriminant analysis(LFDA) as the discriminative term to guide dictionary learning. This method constructed a local within-class scatter matrix to encode the local structure of data space, which enhanced the ability of exploiting the local structure of same class data space and further reflected the local similarity of coding vectors in data space. In order to evaluate the performance of the proposed method for image recognition, the experiment carried on several common datasets. From the experimental result, the proposed method has an obvious improvement over the other competing methods.

Foundation Support

国家自然科学基金资助项目(61602390)
西华大学研究生创新基金资助项目(ycjj2019095)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.11.0607
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 2
Section: Algorithm Research & Explore
Pages: 489-494,500
Serial Number: 1001-3695(2021)02-032-0489-06

Publish History

[2021-02-05] Printed Article

Cite This Article

陈子鎏, 胡高鹏, 王晓明, 等. 基于局部类内结构的鉴别性字典学习方法 [J]. 计算机应用研究, 2021, 38 (2): 489-494,500. (Chen Ziliu, Hu Gaopeng, Wang Xiaoming, et al. Discriminative dictionary learning based on locality intra-class structure [J]. Application Research of Computers, 2021, 38 (2): 489-494,500. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)