台湾林智仁等对如何使用SVM进行多分类的理论、算法以及实验的介绍-Taiwan' s Lin Zhiren, etc. on how to use SVM for multi-classification of the theory, algorithms and experimental introduction of

总结SVM多分类的文章，从训练时间、分类时间、分类器的个数等等入手进行对比-Summary SVM multi-classification of articles, from the training time, classification time, the number of classifiers, and so begin to compare

提出了基于主动学习SVM的局部放电模式识别方法。将主动学习的思想引用到“一对一”多分类SVM分类器,选用基于后验概率的釆样函数对放电样本进行选择,挑选出对分类器最有价值的样本进行训练。 -Puts forward the partial discharge pattern recognition method based on active learning SVM. Will reference to the one to one the ideology of active stud

基于支持向量机方法的图像分割与目标分类.介绍了支持向量机用于车辆图像分类。以及用于单目标图像的分割和多目标图像的分割，介绍的较为详细。-Method of image segmentation based on support vector machine (SVM) and the target classification. This paper introduces the support vector machine (SVM) is used to vehicle image clas