[1]王立国,李阳.融合主动学习的高光谱图像半监督分类[J].哈尔滨工程大学学报,2017,38(08):1322-1327.[doi:10.11990/jheu.201606046]
 WANG Liguo,LI Yang.Semi-supervised classification for hyperspectral image collaborating with active learning algorithm[J].hebgcdxxb,2017,38(08):1322-1327.[doi:10.11990/jheu.201606046]
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
38
期数:
2017年08期
页码:
1322-1327
栏目:
出版日期:
2017-08-25

文章信息/Info

Title:
Semi-supervised classification for hyperspectral image collaborating with active learning algorithm
作者:
王立国 李阳
哈尔滨工程大学 信息与通信工程学院, 黑龙江 哈尔滨 150001
Author(s):
WANG Liguo LI Yang
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
关键词:
高光谱图像半监督分类支持向量机主动学习差分进化
分类号:
TP75
DOI:
10.11990/jheu.201606046
文献标志码:
A
摘要:
针对高光谱数据维数高、有标签样本少等特点,采用半监督分类利用未标记样本信息提高高光谱图像分类精度。主动学习研究训练样本的选择方法,以少量的标记样本得到尽可能好的泛化能力。本文提出了一种结合主动学习算法的半监督分类算法。该方法使用支持向量机作为基本的学习模型,通过主动学习方法选取训练样本,以伪标记的形式加入到分类器的训练中,结合验证分类器迭代选出置信度较高的伪标记样本,通过差分进化算法交叉变异伪标记样本扩充标记样本群。在两个数据集上进行仿真实验,与传统分类算法相比,所提算法的总体分类精度分别提高了1.97%、0.49%,表明该算法能够有效地提升主动学习样本选择的效率,在有限带标记样本情况下提高了分类器精度。

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备注/Memo

备注/Memo:
收稿日期:2016-06-15。
基金项目:国家自然科学基金项目(61675051);黑龙江省自然科学基金项目(F201409).
作者简介:王立国(1974-),男,教授,博士生导师.
通讯作者:王立国,E-mail:wangliguo@hrbeu.edu.cn
更新日期/Last Update: 2017-08-28