基于遗传算法和支持向量机的储粮害虫图像识别 |
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引用本文: | 张建华,朱春华.基于遗传算法和支持向量机的储粮害虫图像识别[J].安徽农业科学,2010,38(17):8833-8834. |
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作者姓名: | 张建华 朱春华 |
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作者单位: | 河南工业大学信息科学与工程学院,河南郑州,450001;河南工业大学信息科学与工程学院,河南郑州,450001 |
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摘 要: | 建立支持向量机(SVM)模型,用遗传算法自动选择最优的核函数参数,利用该SVM与遗传算法相结合的新型算法对储粮害虫图像进行分类识别。结果表明,该方法所确定的SVM对储粮害虫具有较优的识别率,其整体性能优良。
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关 键 词: | 储粮害虫 图像识别 遗传算法 支持向量机 |
Image Recognition of Stored-grain Pests Using SVM and GA |
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Institution: | ZHANG Jian-hua et al(College of Information Science and Technology,Henan University of Technology,Zhengzhou,Henan 450001) |
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Abstract: | A support vector machine(SVM) was established,genetic algorithm(GA) was adopted to automatically select excellent kernel function.A new type algorithm consisting of SVM and GA was used to classify and identify stored-grain pests image.The results showed that the image recognition of stored-grain pests based on SVM and GA was effective. |
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Keywords: | Stored-grain pests Image recognition Genetic algorithm(GA) Support vector Mmachine(SVM) |
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