摘要
提出了一种对存有安全隐患车辆的跟踪学习方法,对传统的在线学习方法进行改进,通过改善学习性能,使算法在不稳定的安全隐患车辆跟踪中发挥作用,实验结果表明,在同等条件下,该算法能够获取更多有效样本,使得分类器更快收敛。
This thesis proposes a tracking method on danger-hiding vehicles, which betters traditional online learning method. Through promoting learning efficiency, this method puts into work in the unstable tracking of danger-hiding vehicles. The experiment data tells that this method, under the same conditions, can get more effective samples and make classifiers having much faster convergence.
关键词
安全隐患
在线学习
跟踪
算法
hiding danger, online learning,tracking, calculating method