最后使用基于LHBP直方图的支持向量机法精确定位文字区域。
Finally, the LHBP-histogram-based SVM is presented to refine the text location.
文章中讨论支持向量机与基础追踪去杂讯法之间的关系。
This is the paper in which the relation between SVM and BPD is studied.
该文首先介绍了构造型神经网络中的覆盖算法的特点和性质，以及与支持向量机(SVM)中的核函数法的关系。
This paper presentes the characteristics, properties and relationship of Covering Algorithms and the kernel function of Support Vector Machines (SVM) firstly.
我们将讨论拔靴集成法与多模激发法，以及这两个演算法是如何成功的被运用。我们也将介绍近来运用与拔靴集成法相似的方法，结合支持向量机所做的一些案例。
We discuss bagging and boosting and suggest some plausible justification for their success. We also describe some recent work about combining SVMs in a way similar to bagging.
这一方法大大提高了支持向量机分类的泛化能力，从而大大提高了支持向量机的应用范围。
This approach greatly improves the generalization ability of SVM classification and its application area is extended.
试验结果表明这种方法是可行的并且分类精度和速度均较传统的支持向量机分类法有所提高。
The results show that this method is feasible and the classification accuracy and speed is better than traditional support vector machine.
为了建立HIV 蛋白酶抑制剂Q SAR的优良模型，本文采用粒子群优化法搜索支持向量机的多参数复杂模型空间，以此形成最优支持向量机。
The optimal support vector machine was proposed in this paper by applying particle swarm optimization searching the complex multi-variable space in SVM model, in order to modeling the better QSAR.
为了验证支持向量机的房地产估价模型的有效性，还与市场比较法及RBF进行了对比分析，得出了几点有意义的结论。
For testing the availability of the model, it analyses the forecast result of the market comparison approach and RBF, finally sums up some meaning conclusion.
为了验证支持向量机的房地产估价模型的有效性，还与市场比较法及RBF进行了对比分析，得出了几点有意义的结论。
For testing the availability of the model, it analyses the forecast result of the market comparison approach and RBF, finally sums up some meaning conclusion.
应用推荐