| 基于改进的支持向量机方法的多目标图像分割 |
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| 引用本文： | 徐海祥,曹万华,陈炜,郭丽艳.基于改进的支持向量机方法的多目标图像分割[J].舰船电子工程,2009,29(2):113-115. |
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| 作者姓名： | 徐海祥 曹万华 陈炜 郭丽艳 |
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| 作者单位： | 1. 哈尔滨工程大学计算机科学与技术学院,哈尔滨,150001;武汉数字工程研究所,武汉,430074
2. 武汉数字工程研究所,武汉,430074 |
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| 摘 要： | 支持向量机方法被看作是对传统学习分累方法的一个好的替代，特别在小样本、高维情况下，具有较好的泛化性能。针对一对一支持向量机方法进行了改进，并采用其对多目标图像进行了分割研究。实验结果表明，支持向量机方法是一种很有前景的图像分割技术。
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| 关 键 词： | 统计学习理论 支持向量机 一对一方法 多目标图像分割 |
Segmentation of Multi-target Image Based on Improved Support Vector Machine Approach |
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| Xu Haixiang,Cao Wanhua,Cheng Wei,Guo Liyuan.Segmentation of Multi-target Image Based on Improved Support Vector Machine Approach[J].Ship Electronic Engineering,2009,29(2):113-115. |
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| Authors: | Xu Haixiang Cao Wanhua Cheng Wei Guo Liyuan |
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| Institution: | College of Computer Science and Technology;Harbin Engineering University1;Wuhan Digital Engineering Institute2 |
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| Abstract: | Support vector machine approach is considered as a good candidate because of its good generalization performance,especially when the number of training samples is very small and the dimension of feature space is very high.In this paper,an improved one-against-one support vector machine is proposed and the segmentation of multi-target image based on the improved one-against-one support vector machine approach is investigated.Experimental results show that support vector machine approach is a promising techni... |
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| Keywords: | statistical learning theory support vector machine one-against-one segmentation of multi-target image |
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