Support Vector Machine For Recognition Of Cucumber Leaf Diseases

摘要：

Support vector machine (SVM) is discussed to use for recognizing cucumber leaf diseases in this paper. Considering that it is a small number of samples, a new experimental program has been proposed which takes each spot of leaves as a sample instead of taking each leaf as a sample. In the experiments Radial Basis Function (RBF), polynomial and Sigmoid kernel function were also used to carry out comparative tests. The results showed that, the SVM method based on RBF kernel function and taking each spot as a sample made the best performance for classification of cucumber leaf diseases.

关键词： pattern recognition support vector machine classification kernel function cucumber leaf disease

作者: Zhang Jian Zhang Wei

作者单位: Institute of Intelligent Machines,Chinese Academy of Sciences,Hefei,China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 264-266

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）