ID 原文 译文
14195 首先提取军事目标的LBP和PHOG特征;然后利用改进的典型相关分析将LBP与PHOG特征相融合。 Firstly‚the LBP and PHOG features of military images are extracted‚and then the extracted features are fused by LDCCA.
14196 最后利用K-最近邻分类器对图像进行分类。 Finally‚K-nearest neighbor classifier is used to classify the military images.
14197 该方法的优点在于LBP与PHOG相融合的特征有比较好的分类能力和鲁棒性。 The advantage of this method is that the fused LBP and PHOG features are robust and able to classify images.
14198 在军事目标数据集上的分类结果表明,该方法是有效可行的。该方法为军事目标识别系统提供了技术参考。 The results on a data set of military targets show that this method is effective and feasible‚which provides a technical reference for the military target identification system.
14199 为了更加完整地描述不确定信息,将三角模糊数与毕达哥拉斯犹豫模糊集结合,提出了毕达哥拉斯三角犹豫模糊集。 In order to describe uncertain information more completely, this paper combines triangular fuzzy numbers with Pythagorean hesitant fuzzy sets, and proposes the concept of Pythagorean Hesitant Triangulai Fuzzy Sets(PHTFS).
14200 针对信息集成过程中数据属性之间存在关联关系的问题,将Heronian平均算子、Muirhead平均算子拓展到毕达哥拉斯三角犹豫模糊集中,提出了毕达哥拉斯三角犹豫模糊Heronian平均算子和毕达哥拉斯三角犹豫模糊Muirhead平均算子。 In view of the association between data attributes in the process of information integration, this paper extends the Heronian mean operator and the Muirhead mean operator to the PHTFS, and proposes the Pythagorean Hesitant Triangular Fuzzy Heronian Mean(PHTFHM) operator and the Pythagorean Hesitant Triangular Fuzzy Muirhead Mean(PHTFMM) operator.
14201 考虑不同属性的输入变量的重要程度不同,提出了它们的加权形式。 In view of different levels of importance of input variables of different attributes, their weighted forms are presented.
14202 最后,针对毕达哥拉斯三角犹豫模糊环境下的多属性决策问题,提出了基于PHTFWMM算子的多属性决策方法,并通过算例说明了该方法的有效性。 Finally, as for the multi-attribute decision-making problem in the Pythagorean hesitant triangular fuzzy environment, a multi-attribute decision. making method based on the Pythagorean Hesitant Triangular Fuzzy Weighted Muirhead Mean(PHTFWMM) operator is proposed, and the effectiveness of this method is illustrated by an example.
14203 针对复杂场景中光照变化、目标自身尺度变化等引起的目标丢失或误跟踪等问题,提出一种尺度和光照自适应的结构化多目标跟踪方法。 In complex scenes, illumination variation and changes in the target's scale may lead to loss of targets or mis-tracking.
14204 利用多尺度Retinex算法对序列图像进行预处理; To solve the problem, this paper proposes a structured multi-target tracking algorithm adaptive to scale and illumination changes.