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1.
Wonje Jang Junhyuk Hyun Jhonghyun An Minho Cho Euntai Kim 《IEEE/CAA Journal of Automatica Sinica》2022,9(1):187-204
The essential requirement for precise localization of a self-driving car is a lane-level map which includes road markings (RMs). Obviously, we can build the lane-level map by running a mobile mapping system (MMS) which is equipped with a high-end 3D LiDAR and a number of high-cost sensors. This approach, however, is highly expensive and ineffective since a single high-end MMS must visit every place for mapping. In this paper, a lane-level RM mapping system using a monocular camera is developed. The developed system can be considered as an alternative to expensive high-end MMS. The developed RM map includes the information of road lanes (RLs) and symbolic road markings (SRMs). First, to build a lane-level RM map, the RMs are segmented at pixel level through the deep learning network. The network is named RMNet. The segmented RMs are then gathered to build a lane-level RM map. Second, the lane-level map is improved through loop-closure detection and graph optimization. To train the RMNet and build a lane-level RM map, a new dataset named SeRM set is developed. The set is a large dataset for lane-level RM mapping and it includes a total of 25157 pixel-wise annotated images and 21000 position labeled images. Finally, the proposed lane-level map building method is applied to SeRM set and its validity is demonstrated through experimentation. 相似文献
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The ordered weighted averaging (OWA) operators play a crucial role in aggregating multiple criteria evaluations into an overall assessment supporting the decision makers’ choice. One key point steps is to determine the associated weights. In this paper, we first briefly review some main methods for determining the weights by using distribution functions. Then we propose a new approach for determining OWA weights by using the regular increasing monotone quantifier. Motivated by the idea of normal distribution-based method to determine the OWA weights, we develop a method based on elliptical distributions for determining the OWA weights, and some of its desirable properties have been investigated. 相似文献
4.
In multicriteria decision-making (MCDM), the existing aggregation operators are mostly based on algebraic t-conorm and t-norm. But, Archimedean t-conorms and t-norms are the generalized forms of t-conorms and t-norms which include algebraic, Einstein, Hamacher, Frank, and other types of t-conorms and t-norms. From that view point, in this paper the concepts of Archimedean t-conorm and t-norm are introduced to aggregate Pythagorean hesitant fuzzy information. Some new operational laws for Pythagorean hesitant fuzzy numbers based on Archimedean t-conorm and t-norm have been proposed. Using those operational laws, Archimedean t-conorm and t-norm-based Pythagorean hesitant fuzzy weighted averaging operator and weighted geometric operator are developed. Some of their desirable properties have also been investigated. Afterwards, these operators are applied to solve MCDM problems in Pythagorean hesitant fuzzy environment. The developed Archimedean aggregation operators are also applicable in Pythagorean fuzzy contexts also. To demonstrate the validity, practicality, and effectiveness of the proposed method, a practical problem is considered, solved, and compared with other existing method. 相似文献
5.
为提高稀疏表示跟踪模型性能,提出一种分段加权的反向稀疏跟踪算法,将跟踪问题转化为在贝叶斯框架下寻找概率最高的候选对象问题,构造不同的分段权重函数来分别度量候选目标与正负模板的判别特征系数。通过池化来降低跟踪结果的不确定性干扰,选择正负模板加权系数差值最大的候选表示作为跟踪结果。实验表明,在光照变化、遮挡、快速运动、运动模糊情况下,所提出的算法可以确保跟踪结果的准确性和鲁棒性。 相似文献
6.
Wen Sheng Du 《国际智能系统杂志》2019,34(11):2835-2862
Weighted power means with weights and exponents serving as their parameters are generalizations of arithmetic means. Taking into account decision makers' flexibility in decision making, each attribute value is usually expressed by a -rung orthopair fuzzy value ( -ROFV, ), where the former indicates the support for membership, the latter support against membership, and the sum of their th powers is bounded by one. In this paper, we propose the weighted power means of -rung orthopair fuzzy values to enrich and flourish aggregations on -ROFVs. First, the -rung orthopair fuzzy weighted power mean operator is presented, and its boundedness is precisely characterized in terms of the power exponent. Then, the -rung orthopair fuzzy ordered weighted power mean operator is introduced, and some of its fundamental properties are investigated in detail. Finally, a novel multiattribute decision making method is explored based on developed operators under the -rung orthopair fuzzy environment. A numerical example is given to illustrate the feasibility and validity of the proposed approach, and it is shown that the power exponent is an index suggesting the degree of the optimism of decision makers. 相似文献
7.
针对人脸识别因光照、姿态、表情、遮挡及噪声等多种因素的影响而导致的识别率不高的问题,提出一种加权信息熵(IEw)与自适应阈值环形局部二值模式(ATRLBP)算子相结合的人脸识别方法(IE (w) ATR-LBP)。首先,从原始人脸图像分块提取信息熵,得到每个子块的IEw;然后,利用ATRLBP算子分别对每个人脸子块提取特征从而得到概率直方图;最后,将各个块的IEw与概率直方图相乘,再串联成为原始人脸图像最后的特征直方图,并利用支持向量机(SVM)对人脸进行识别。在AR人脸库的表情、光照、遮挡A和遮挡B四个数据集上,IE (w) ATR-LBP方法分别取得了98.37%、94.17%、98.20%和99.34%的识别率。在ORL人脸库上,IE (w) ATR-LBP方法的最大识别率为99.85%;而且在ORL人脸库5次不同训练样本的实验中,与无噪声时相比,加入高斯和椒盐噪声后的平均识别率分别下降了14.04和2.95个百分点。实验结果表明,IE (w) ATR-LBP方法能够有效提高人脸在受光照、姿态、遮挡等影响时的识别率,尤其是存在表情变化及脉冲类噪声干扰时的识别率。 相似文献
8.
为联合可见/近红外光谱技术和变量选择方法在线检测脐橙主要内部品质指标可溶性固形物(SSC),分别选定脐橙校正集和预测集样本141个和47个,脐橙运输速度为0.3m/s,利用USB4000微型光谱仪在线采集脐橙样本的可见/近红外光谱,先分别采用无信息变量消除(UVE)和遗传算法(GA)对650~950nm波段范围的波长变量进行预筛选,再分别利用竞争自适应重加权采样(CARS)及连续投影算法(SPA)对波长变量进一步筛选,并应用偏最小二乘(PLS)方法分别建立脐橙SSC的在线预测模型,并与原始光谱等建立的预测模型进行比较。结果表明,对于脐橙SSC,预筛选方法GA优于UVE方法,变量选择方法CARS优于SPA方法;GA-CARS及GA-SPA联合变量选择方法优于对应的单一变量选择方法CARS及SPA。在上述变量选择方法中,GA-CARS方法获得的结果最优,其所建立的脐橙SSC的PLS模型的校正集和预测集相关系数分别为0.933和0.824,校正集和预测集均方根误差分别为0.429%和0.670%,性能优于原始光谱建立的PLS模型,且建模波长变量数由1 385个下降为78个,仅占原波长变量数的5.63%。由此表明,GA-CARS联合变量选择方法可以有效筛选脐橙SSC的波长变量,提高预测模型的稳定性和预测精度。 相似文献
9.
近年来,我国传统暴力犯罪与成年人犯罪呈下降态势,但是,犯罪案由层出不穷。为有效提升公安实践工作中犯罪预测能力,打击各类违法犯罪事件,本文针对犯罪数据,提出一种新型犯罪预测模型。利用密度聚类分析方法将犯罪数据分类,然后进行数据降维提取关键属性生成特征数据,继而对特征数据进行加权优化并采用机器学习的方式对特征数据进行学习,从而预测犯罪案由。实验结果表明,与传统方法相比,本文方法具有更好的预测效果,为公安实践工作中类似案件的侦破和预防,提供新的路径支撑。 相似文献
10.
针对长期演进(LTE)移动通信系统下行链路传输中多用户的实时(RT)与非实时(NRT)业务传输性能需求问题,提出一种基于用户加权平均时延的改进型的最大加权延时优先(MLWDF)资源调度算法。该算法在考虑信道感知与用户服务质量(QoS)感知的基础上引入反映用户缓冲区状态的加权平均时延因子,该因子通过用户缓冲区中待传输数据与已发送数据的平均时延均衡得到,使具有较大时延和业务量的实时业务优先调度,提升了用户的性能体验。理论分析与链路仿真表明,提出算法在保证各业务时延及公平性的基础上,提升了实时业务的QoS性能,在用户数量达到50的条件下,对比MLWDF算法实时业务的丢包率降低了53.2%,其用户平均吞吐量提升了44.7%,虽牺牲了非实时业务的吞吐量,但仍优于VT-MLWDF算法。实验结果表明,所提算法在多用户多业务传输条件下提升了实时业务的传输性能,并在QoS性能上明显优于对比算法。 相似文献