Space Target Recognition Method Based on Improved Adaboost Algorithm
DOI:
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Due to the non-cooperative character of space target and the overfitting of adaboost algorithm under high noises, an space target recognition method based on combined features and improved adaboost is proposed. The combined features which consist of the geometric features and transform features are extracted to describe target information precisely from different aspects. Furthermore, an improved adaboost algorithm is presented, which adopts a new weights updating method piecewisely in the light of the weights distribution of samples. Thus the proposed method can avoid the overfitting problem and improve the robustness of classification. Experiments on space target images showed that the proposed method has better classification capability and obtains higher classification accuracy.

    Reference
    Related
    Cited by
Get Citation

李垒,任越美.基于改进Adaboost集成学习的空间目标识别.计算机系统应用,2015,24(8):202-205

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:December 19,2014
  • Revised:February 09,2015
  • Adopted:
  • Online: September 03,2015
  • Published:
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063