| 一类支持向量机在车辆识别中的应用 |
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| 引用本文： | 孙德山,吴今培.一类支持向量机在车辆识别中的应用[J].交通运输系统工程与信息,2003,3(4):34-37. |
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| 作者姓名： | 孙德山 吴今培 |
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| 作者单位： | 1.中南大学数学科学与计算技术学院，长沙410075； 2.辽宁师范大学数学系，大连，116029；3. 五邑大学智能技术与系统研究所，江门529020 |
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| 基金项目： | 广东省自然科学基金资助(021349). |
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| 摘 要： | 支持向量机分类方法已经在实际应用中显示了良好的学习性能，其最初是针对二值分类问题提出的.如何有效地将支持向量机推广到多值分类中一直是人们关注的课题.通常的多值分类问题是一系列二值分类来实现，可是这将导致较高的计算复杂性.本文将一类支持向量机推广到多值分类情况，并将其应用于车辆识别中.仿真实验结果表明了所给方法的可行性及有效性.
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| 关 键 词： | 一类支持向量机 核函数 多值分类 车辆识别 |
| 文章编号： | 1009-6744(2003)04-0034-04 |
| 收稿时间： | 2003-09-17 |
| 修稿时间： | 2003年9月17日 |
Vehicle Recognition Based on 1-SVM |
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| SUN De- shan,WU Jin-pei.Vehicle Recognition Based on 1-SVM[J].Transportation Systems Engineering and Information,2003,3(4):34-37. |
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| Authors: | SUN De- shan WU Jin-pei |
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| Affiliation: | 1. School of Mathematical Science and Computing Technology, Central South University, Changsha 410075, China；2.Department of Mathematics, Liaoning Normal University, Dalian 116029, China；3.Institute of Intelligent Technology & System, Wuyi University, Jiangmen 529020, China |
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| Abstract: | The Support Vector Machine (SVM) has shown excellent performance in practice as a classification methodology, which were originally designed for binary classification. How to effectively extend SVM for multi-class classification is still an on-going research issue. Oftentimes multi-class classification problem have been treated as a series of binary problems in the SVM paradigm, but it is computationally more expensive to solve multi-class problems. In this paper, a new multi-class classification method is proposed based on one-class support vector machine (1-SVM), and then applies the method to vehicle recognition. The results of simulation experiments at vehicle database show that the proposed method is effective and feasible. |
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| Keywords: | 1-SVM kernel function multi-class classification vehicle recognition |
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