A Modified AdaBoost Algorithm with New Discrimination Features for High-Resolution SAR Targets Recognition-Reference-Cited by-同舟云学术

A Modified AdaBoost Algorithm with New Discrimination Features for High-Resolution SAR Targets Recognition

Published:2015 Issue:10 Volume:E98.D Page:1871-1874
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

CHEN Kun¹,LI Yuehua¹,XU Xingjian¹,LI Yuanjiang²

Affiliation:

1. School of Electronic and Optical Engineering, Nanjing University of Science and Technology

2. Institute of Electronic and Information, Jiangsu University of Science and Technology

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E98.D/10/E98.D_2015EDL8090/_pdf

Reference11 articles.

1. [1] D.E. Dudgeon and R.T. Lacoss, “An overview of automatic target recognition,” Lincoln Lab. J., vol.6, no.1, pp.3-10, 1993.

2. [2] A.K. Mishra, “Validation of PCA and LDA for SAR ATR,” in TENCON-IEEE Region 10 conference, Hyderabad, India, 2008, 1-6.

3. [3] Q. Zhao and J.C. Principe, “Sopport vector machines for SAR automatic target recognition,” IEEE Trans. Aerosp. Electron. Syst., vol.37, no.2, pp.643-654, 2001.

4. [4] S. Roweis and L. Saul, “Nonlinear dimensionality reduction by locally linear embedding,” Science, vol.290, n0.5500, pp.2323-2326, 2000.

5. [5] S. Wang, P. Pan, and Y. Lu, “An adaptive multiclass boosting algorithm for classification” in: Proceeding of International joint conference on Neural Networks (IJCNN). pp.1159-1166, Beijing, China, 2014.

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