山东农业大学学报（自然科学版）Issue(z1)：150-156,7.DOI:10.3969/j.issn.1000-2324.2014.z.034
邻域核局部支持向量机在图像分类中的研究
Application of Neighborhood Local Support Vector Machine in Image Classification
摘要
Abstract
Local Support Vector Machine can effectively use the local information of samples. Compared with the standard Support Vector Machine, it has higher classification accuracy. The neighborhood kernel function can make effective use of neighborhood change information. This paper proposes a novel Local Support Vector Machine algorithm based on neighborhood kernel function and used it in image classification. In order to verify the validity of the method, this paper did tests using image data. The experimental results show that, this novel LSVM has higher classification accuracy than SVM and LSVM. So it can effectively improve the accuracy of image classification.关键词
邻域核函数/局部支持向量机/分类Key words
Neighborhood kernel function/local support vector machine/classification分类
信息技术与安全科学引用本文复制引用
浩庆波,牟少敏,尹传环,王秀美..邻域核局部支持向量机在图像分类中的研究[J].山东农业大学学报（自然科学版）,2014,(z1):150-156,7.基金项目
国家自然科学青年基金(61105056) （61105056）
山东省自然科学基金(ZR2012FM024) （ZR2012FM024）
2013年山东省农业重大应用技术创新课题 （）
