| ID | 原文 | 译文 |
| 51217 | 六自由度仿真结果表明了该制导律的有效性。 | Simulation results show the effectiveness of the proposed guidance law. |
| 51218 | 在线多示例目标跟踪算法无法判别目标丢失以及无法适应目标尺度的变化。 | Online sample target tracking algorithm can't distinguish more lost and unable to adapt to changes in the target dimension. |
| 51219 | 提出了一种基于视觉字典的在线多示例目标跟踪算法。 | Put forward a kind of online sample more target tracking algorithm based on visual dictionary. |
| 51220 | 算法将视觉字典和多示例跟踪分别作为检测器和跟踪器，利用互反馈技术提高跟踪性能。 | Algorithm and the visual dictionary more sample tracking as a detector and tracker, respectively using mutual feedback technology to improve the tracking performance. |
| 51221 | 跟踪器完成目标的跟踪并为视觉字典的构建和更新提供训练样本; | Tracking target tracking and provide visual dictionary construction and update the training sample; |
| 51222 | 检测器则对跟踪器的结果(候选样本)进行判定， | Detector is the results of the tracker to identify (candidate), |
| 51223 | 目标丢失时，暂停跟踪并重新检测目标， | the target is lost, the suspension of target tracking and detection, |
| 51224 | 目标未丢失时，利用Ransac算法获得目标的尺度变换系数并在新尺度下更新跟踪器。 | the target is not lost, use Ransac algorithm to obtain the scale of the target transform coefficient and update the tracker in the new scale. |
| 51225 | 为了提高目标丢失判别的准确性，提出了一种局部随机抽样的直方图相似性度量技术， | In order to improve the accuracy of target loss criterion, this paper proposes a local histogram similarity measure technology of random sampling, |
| 51226 | 采用局部划分思想和Noisy-NR模型计算候选样本与训练样本特征直方图的相似性， | the idea of local division and Noisy - NR model candidate sample and training sample feature histogram similarity, |