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基于复杂网络特性的带钢表面缺陷识别

DOI: 10.3724/SP.J.1004.2011.01407, PP. 1407-1412

Keywords: 缺陷识别,复杂网络特征,主成分分析法,有向无环图支持向量机

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Abstract:

?针对带钢表面缺陷识别问题,提出一种基于动态演化复杂网络特性的特征描述方法,这些特征同时具有位移、旋转不变性、大小不变性、较强的抗干扰能力和鲁棒性,为缺陷识别提供良好的分类特征;为了提高分类器的效率,应用主成分分析法(Principalcomponentanalysis,PCA)对复杂网络特征向量进行特征降维处理;采用最优有向无环图支持向量机(Directedacyclicgraphsupportvectormachine,DAG-SVM)算法进行缺陷分类.结果表明该方法识别率高而且识别速度快.

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