ID 原文 译文
23005 再次，计算显著-深度矫正概率，并对深度图的初步显著检测结果使用此概率进行矫正。 After that, Saliency-Depth (S-D) rectify probability is also computed and the saliency results of depth images are corrected with this probability.
23006 接着，计算基于 RGB 的显著中心先验，并以该先验作为显著权重进一步提升深度图像矫正后的显著检测结果，获取深度图像的最终显著图； Then the saliency center prior based on RGB is also computed and this value is used as saliency weights to further improve the depth image saliency detection results and to obtain the final depth saliency maps.
23007 最后，采用优化框架对深度图像最终显著图进行优化得到 RGB-D 图像最终的显著图。 Finally the optimization framework is utilized to optimize the depth image final saliency maps and to obtain the final RGB-D saliency map.
23008 所有的对比实验都是在公开的数据集 NLPR RGBD-1000 数据集上进行，实验结果显示该文算法较当前流行的算法有更好的性能。 All the experiments are executed on the public NLPR RGBD-1000 benchmark and extensive experiments demonstrate that the proposed algorithm achieves better performance compared with existing state-of-the-art approaches.
23009 该文提出一种新的绝对误差函数，应用该函数进行非线性模型参数提取可以避免计算误差，显著降低参数提取的不准确性。 A new absolute error function is presented in this paper. The function is applied to extract parameters of the nonlinear model, which can avoid the calculation error and reduce the inaccurate parameter extraction significantly.
23010 由于氮化物半导体器件，尤其是 AlGaN/GaN HEMT 器件已经开始得到广泛应用，其模型和参数对射频和电力电子器件和电路设计至关重要，分别使用 3 种误差函数对  AlGaN/GaN HEMT 器件模型进行了参数提取并对比，对比结果表明该文提出的误差函数更加精确和有效。 Nitride semiconductor devices are widely used, especially the AlGaN/GaN HEMT devices. The AlGaN/GaN HEMT model and parameters is very important to radio frequency, power electronic devices and circuit design. The new absolute error function is applied to extract the parameters of AlGaN/GaN HEMT nonlinear devices model. Through comparing three kinds of error function, the results show that the proposed error function is more accurate and effective.
23011 同时为今后的电子器件的模型参数提取提供了一种有效且精确的方法。 At the same time, a precise and effective method is provided to extract the parameters of electronic devices in the future.
23012 相干变化检测(CCD)利用重轨 SAR 数据对场景中表现为低相干特性的变化区域具有良好的检测性能，然而场景中诸如植被、阴影、强散射旁瓣、低散射等区域也呈现低相干特性，对检测结果造成干扰，尤其在高波段SAR CCD 中，对检测效果影响更加明显。 Coherent Change Detection (CCD) has good performance on detecting change regions with low coherence in the scene by using repeat-pass Synthetic Aperture Radar (SAR) data. However, some regions as vegetation, radar shadows, sidelobes of strong reflectivity and low reflectivity areas show low coherent character as well, which disturbs the result of change detection, especially in high frequency band SAR CCD with more evident disturbance.
23013 该文利用多时相 SAR 数据形成的相干变化差异图像(CCD 图像)建立概率图模型，提出一种多时相 CCD 处理方法。 This paper proposes a multi-temporal CCD method by establishing a probabilistic graphical model using CCD images formed by multi-temporal SAR data.
23014 该方法以多时相 CCD 图像作为观测量，通过选取合适的参与处理图像数量及优化场景中变化区域的分类，计算目标变化区域的后验概率，可有效减小低相干干扰区域造成的影响。 In this method, multi-temporal CCD images are used as observations to calculate a posterior probability of objective change region via choosing appropriate number of processing CCD images and optimizing the classification of change regions in the scene. The proposed method can reduce the disturbance of low coherence disturb regions effectively.