ID 原文 译文
24885 该滤波器采用均值未知且时变的多维 Student’s t 分布对统计特性未知的闪烁噪声进行建模。 The glint noise with unknown statistical characteristics is modeled as a multivariate Student's distribution with unknown and time-varying mean.
24886 它放宽了闪烁噪声均值为零的限制性假设，可以自适应地处理闪烁噪声均值未知且时变条件下的多目标跟踪问题。 The proposed filter relaxes the restrictive assumption that the mean of glint noise is zero, and can effectively deal with the problem of MTT under the condition that the mean of glint noise is unknown and time-varying.
24887 本文在 GLMB 滤波框架下，利用变分贝叶斯方法对增广状态中的参数进行变分迭代，并通过最小化Kullback-Leibler 散度得到边缘似然函数的近似解。 The variational Bayesian approximation is applied in the GLMBfiltering framework with the augmented state. The approximate solution of the marginal likelihood function can be obtained by minimizing the Kullback-Leibler divergence.
24888 仿真结果表明，在闪烁噪声统计特性未知的情况下，所提滤波器能有效地对多目标进行跟踪。 The simulation results demonstrate that the proposed filter can effectively track multi-target when the statistics of glint noise is unknown.
24889 显著性目标检测旨在对图像中最显著的对象进行检测和分割，是计算机视觉任务中重要的预处理步骤之一，且在信息检索、公共安全等领域均有广泛的应用。 Salient object detection aims to detect and segment the most salient objects in the image. It is one of the important preprocessing steps in computer vision tasks, and it has a wide range of applications in information retrieval, public safety and other fields.
24890 本文对近期基于深度学习的显著性目标检测模型进行了系统综述，从检测粒度的角度出发，综述了将深度学习引入显著性目标检测领域之后的研究成果。 This paper systematically reviews the recent research on the salient object detection models based on deep learning. From the perspective of detection granularity, the research results of applying deep learning into the field of salient object detection are reviewed.
24891 首先，从三个方面对显著性目标检测方法进行了论述：稀疏检测方法，密集检测方法以及弱监督学习下的显著性目标检测方法。 First, the salient object detection methods are discussed from three aspects. sparse detection methods, dense detection methods and weakly-supervised learning methods.
24892 然后，简要介绍了用于显著性目标检测研究的主流数据集和常用性能评价指标，并对各类主流模型在三个使用最广泛的数据集上进行了性能比较分析。 Then, the mainstream data sets and common performance evaluation indicators used for salient object detection research are briefly introduced, and the performance of various mainstream models on the three most widely used data sets are compared and analyzed.
24893 最后，本文分析了显著性目标检测领域目前存在的问题，并对今后可能的研究趋势进行了展望。 Finally, this paper analyzes the current problems in the field of salient object detection and prospects for possible future research trends.
24894 动态视觉传感器（Dynamic Vision Sensor，DVS）相比于传统彩色相机有更高的时间分辨率、动态范围，且功耗更低、带宽更低，在自动驾驶领域有很好的应用前景，因此吸引了越来越多研究者的注意。 Compared with the traditional color cameras, the dynamic vision sensor, a type of event-based sensor, has higher time resolution, dynamic range, lower power consumption and lower bandwidth requirements. It has good application prospects in the field of automatic driving, which attracts more and more researchers' attention.