| 支持向量机在黄瓜病害识别中的应用研究 |
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| 引用本文： | 田有文,牛妍.支持向量机在黄瓜病害识别中的应用研究[J].农机化研究,2009,31(3). |
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| 作者姓名： | 田有文 牛妍 |
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| 作者单位： | 沈阳农业大学,信息与电气工程学院,沈阳,110161 |
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| 基金项目： | 辽宁省自然科学基金，辽宁省教育厅攻关计划 |
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| 摘 要： | 探讨了采用支持向量机对黄瓜病害进行分类的方法;提取了病斑的形状、颜色、质地、发病时期等特征作为特征向量,利用支持向量机分类器,选取4种常见核函数,以Matlab7.0为平台对10类常见病害进行识别.结果表明,SVM 方法在处理小样本问题中具有良好的分类效果,线性核函数和径向基核函数的SVM 分类方法在黄瓜病害的识别方面优于其他类型核函数的SVM.
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| 关 键 词： | 分类识别 支持向量机 黄瓜病害 特征选取 |
Applied Research of Support Vector Machine on Recognition of Cucumber Disease |
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| Tian Youwen,Niu Yan.Applied Research of Support Vector Machine on Recognition of Cucumber Disease[J].Journal of Agricultural Mechanization Research,2009,31(3). |
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| Authors: | Tian Youwen Niu Yan |
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| Institution: | College of Information and Electrical Engineering;Shenyang Agricultural University;Shenyang 110161;China |
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| Abstract: | Classification of cucumber diseases had been discussed by support vector Machine.First,we extracted the shape,color,texture,onset period of diseased spots as feature vector,then created svm classifier by four common functions. Ten kinds of cucumber diseases had been classified in Matlab7.0 platform.The results show us that the method of svm has better performance in solving small sample problems,and the classification based on linear kernel function and rbf kernel function is better than other functions on ... |
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| Keywords: | classification and recognition support vector machine cucumber disease feature extracted |
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