ID 原文 译文
25865 然后，采用核协同表示和鉴别投影思想进行降维学习和字典学习，以提升数据低维表征和类间鉴别能力; Then, the kernel collaborative representation and discriminative projection ideas are used to complete the dimensionality reduction learning and dictionary learning to improve the low-dimensional representation and inter-class discrimination capabilities of the data．
25866 最后，通过离线训练完成系统优化并用于分类验证。 Finally, the system is optimized through offline training and used for classification verification．
25867 仿真结果表明，二次时频分布特征具备较高稳定性，识别方法具备较强鲁棒性、时效性和适应性; Simulation results show that the secondary time-frequency distribution feature has high stability, and the recognition method has strong robustness, timeliness and adaptability．
25868 当信噪比为 － 10dB 时，该方法对 8 类辐射源信号的整体平均识别率达到 96. 88% 。 When the SNR is － 10dB，the overall average recognition rate of the eight signals reaches 96. 88% ．
25869 针对施工现场环境复杂，难以高效管理的问题． 提出了基于工地场景的深度学习目标跟踪算法，辅助施工顺利进行。 Construction site is difficult to be effectively managed owing to its complex environment. A deep learning target tracking algorithm based on construction site scene is proposed to assist the construction progress．
25870 根据工地现场目标的连续性，构建增强群跟踪器，提升目标成功跟踪的概率。 Firstly, according to the continuity of the target in the site scene, the enhanced group tracker is constructed to improve the successful probability of target tracking．
25871 然后从滑动窗口、StackedDenoising Auto Encoder(SDAE)和 Support Vector Machine(SVM)三方面组建深度检测器。 Then, the depth detector is constructed with sliding window, stacked denoising auto encoder (SDAE) and support vector machine (SVM)．
25872 在滑动窗口方面:从梯度角度建立模型实现窗口自适应。 Sliding window: a model is built from the gradient angle to realize window adaption．
25873 在 SDAE 算法方面:构建反向算法微调网络参数。 SDAE algorithm: the reverse algorithm is built to fine-tune network parameters．
25874 优化 SVM 算法降低跟踪时目标漂移和跟踪失败的概率，最终实现目标高精度跟踪。 Optimized SVM algorithm reduces the probability of target drift and tracking failure. Finally, high precision tracking is achieved．