检索结果-内蒙古大学图书馆

26th International Conference on Information Fusion, FUSION 2023

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Xue, Yanbo University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Career Science Lab Beijing China

ISBN: (纸本)9798890344854

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target. © 2023 International Society of Information Fusion.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

YOLOv5s-SLAM: A Monocular Visual SLAM method in Dynamic Environments 9

YOLOv5s-SLAM: A Monocular Visual SLAM method in Dynamic Envi...

引用

9th International Conference on computer and Communications, ICCC 2023

作者： Yin, Zhenyu Feng, Dan Fan, Chao Wang, Xiaohui Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China University of Chinese Academy of Sciences School of Computer Science and Technology Shenyang110168 China Liaoning Key Lab. of Domestic Industrial Control Platform Technology on Basic Hardware Software Shenyang110168 China

ISBN: (纸本)9798350317251

To deal with the problem that traditional visual SLAM methods in dynamic environments are susceptible to the influence of moving targets, which leads to a decrease in the system's localization accuracy. This paper presents a dynamic visual SLAM system named YOLOv5s-SLAM. YOLOv5s is embedded in the ORB-SLAM3 system to recognize dynamic targets in the surrounding environment by deep learning methods and simultaneously extract ORB feature points with the SLAM system at the front end as a way to improve real-time performance. Combined with the constructed dynamic object detection rules, the dynamic feature points are divided and removed, which effectively reduces the mismatching in the feature extraction process and the impact on the system performance, and achieves the optimization of the visual SLAM localization performance. Tests on the TUM dataset show that the proposed method has smaller trajectory errors and higher position estimation accuracy, which can effectively enhance the robustness of localization. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

SP-VSLAM:Monocular Visual-SLAM Algorithm Based on SuperPoint Network 15

SP-VSLAM:Monocular Visual-SLAM Algorithm Based on SuperPoint...

引用

15th International Conference on Communication Software and Networks, ICCSN 2023

作者： Yin, Zhenyu Feng, Dan Fan, Chao Ju, Chengen Zhang, Feiqing Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China School of Computer Science and Technology University of Chinese Academy of Sciences Shenyang110168 China Liaoning Key Lab. of Domestic Industrial Control Platform Technology on Basic Hardware Software Shenyang110168 China

ISBN: (纸本)9798350329360

For scenes with significant changes in light intensity or perspective, the traditional ORB feature extraction method is prone to the problems of local homogenization of feature points and errors arising from the accumulated drift. A monocular visual Simultaneous Localization and Mapping algorithm (SLAM) based on SuperPoint network (SP-VSLAM) is proposed. The SuperPoint network is used to extract feature points and calculate binary descriptors simultaneously, combined with Non-Maximal Suppression methods to achieve uniform detection and description of image feature points. Then construct robust and accurate feature association information. It is fused with the back-end local mapping, loop & map merging modules of the ORB-SLAM3 system to construct a complete monocular vision SLAM system. Using the public measurement datasets TUM, the localization accuracy is calculated for five sequences in monocular mode, and the experimental results show that the proposed method has smaller trajectory error and higher pose estimation accuracy in static, partial low dynamic and high dynamic environments, which can effectively enhance the robustness of tracking. © 2023 IEEE.

关键词： Conformal mapping

来源：评论

学校读者我要写书评

暂无评论

On the Gaussian Filtering for Nonlinear Dynamic Systems Using Variational Inference 27

On the Gaussian Filtering for Nonlinear Dynamic Systems Usin...

引用

27th International Conference on Information Fusion, FUSION 2024

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Li, Ji University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Locaris Electronic Technology Co. Ltd Zhengzhou China

ISBN: (纸本)9781737749769

This paper introduces a new variational Gaussian filtering approach for estimating the state of a nonlinear dynamic system. We first assume that the predictive distribution of the state is Gaussian and derive an iterative method for updating the state posterior in the natural parameter space through KullbackLeibler divergence minimization. The obtained update rule is the same as that of the conjugate-computation variational inference technique in Bayesian learning. The derivation here is simpler and more insightful. We then impose a Wishart prior on the inverse of the state prediction covariance to take into account the impact of approximating the state predictive distribution using a Gaussian density on the state posterior estimation. The prediction covariance is identified jointly with the state using variational inference and the established state posterior update rule to achieve the desired Gaussian filtering. Simulation study examines the performance of the proposed filtering framework in target tracking based on bearing and range measurements. © 2024 ISIF.

关键词： Wiener filtering

来源：评论

学校读者我要写书评

暂无评论

Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

引用

computers, Materials & Continua 2024年第11期81卷 2357-2394页

作者： Altaf Hussain Shuaiyong Li Tariq Hussain Razaz Waheeb Attar Farman Ali Ahmed Alhomoud Babar Shah School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqing400065China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063Republic of Korea Department of Computer Science College of ScienceNorthern Border UniversityArar91431Saudi Arabia College of Technological Innovation Zayed UniversityDubai19282United Arab Emirates

Ad hoc networks offer promising applications due to their ease of use,installation,and deployment,as they do not require a centralized control *** these networks,nodes function as senders,receivers,and *** such network is the Flying Ad hoc Network(FANET),where nodes operate in three dimensions(3D)using Unmanned Aerial Vehicles(UAVs)that are remotely *** the integration of the Internet of Things(IoT),these nodes form an IoT-enabled network called the Internet of UAVs(IoU).However,the airborne nodes in FANET consume high energy due to their payloads and low-power *** optimal routing approach for communication is essential to address the problem of energy consumption and ensure energy-efficient data transmission in *** paper proposes a novel energy-efficient routing protocol named the Integrated Energy-Efficient Distributed Link Stability Algorithm(IEE-DLSA),featuring a relay mechanism to provide optimal routing with energy efficiency in *** energy efficiency of IEE-DLSA is enhanced using the Red-Black(R-B)tree to ensure the fairness of advanced energy-efficient *** link stability,transmission loss avoidance,delay awareness with defined threshold metrics,and improving the overall performance of the proposed protocol are the core functionalities of *** simulations demonstrate that the proposed protocol performs well compared to traditional FANET routing *** evaluation metrics considered in this study include network delay,packet delivery ratio,network throughput,transmission loss,network stability,and energy consumption.

关键词： FANET UAV internet of UAVs relay mechanism energy consumption routing IEE-DLSA

来源：评论

学校读者我要写书评

暂无评论

Research on Transient control Performance Improvement of Complex control System in Nuclear Power Plant 1

引用

6th International Symposium on Software Reliability, industrial Safety, Cyber Security and Physical Protection of Nuclear Power Plant, ISNPP 2021

作者： Luan, Zhen-hua Chen, Rui Liu, Dao-guang Yan, Xin-hong Liang, Jun State Key Lab of Industrial Control Technology College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou310027 China State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment Guangdong Shenzhen518172 China Shandong Business College Shandong Yantai264003 China

ISBN: (数字)9789811911811

ISBN: (纸本)9789811911804

Aiming at the problem that the control performance of nuclear power unit after parameter optimization cannot meet the requirements of transient conditions. A standardized method to improve the transient control performance through logic optimization and operation optimization is proposed. This method consists of parameter optimization, control logic optimization, operating condition optimization and instrument/actuator optimization. It realizes the stable operation of nuclear power unit and the effective control of transient. The results of control system optimization of several nuclear power units show that this method can reduce the risk of transient operation of the control system, improve the operation quality of the unit, and obtain good economic and safety benefits. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Nuclear power plants

来源：评论

学校读者我要写书评

暂无评论

Weighted Fusion of Multiple Classifiers for Human Activity Recognition 26

Weighted Fusion of Multiple Classifiers for Human Activity R...

引用

26th International Conference on Information Fusion, FUSION 2023

作者： Zuo, Kezhu Li, Xinde Dezert, Jean Dong, Yilin Southeast University School of Cyber Science and Engineering Nanjing China Southeast University Key Laboratory of Measurement and Control of Cse School of Automation Nanjing China The French Aerospace Lab Onera DTIS/MIDL Palaiseau France Shanghai Maritime University College of Computer Science and Engineering Shanghai China

ISBN: (纸本)9798890344854

Human Activity Recognition (HAR) based on wear-able device has become a hot topic of research due to its wide range of applications in health-care, fitness and smart homes. However, the classification of some activities with similar sensor readings, such as standing and sitting, is usually more challenging for the design of efficient activity recognition algorithms. Considering the inconsistent performance of different classifiers, which can provide information complementary for individual classifier, we propose a novel multi-classifier fusion method based on belief functions (BFs) theory for HAR. Specifically, at first, four classifiers are trained using time-domain and frequency-domain features to obtain basic belief assignments (BBA) of activity, respectively. Then, three assessment criteria are utilized to evaluate the reliability of the classifiers and a scoring matrix is constructed. Next, the algorithm of Belief Function based the Technique for Order Preference by Similarity to Ideal Solution (BF-TOPSIS) is employed to calculate the weighting coefficients for each classifier. Finally, the discounting and Dempster's rules are adopted to combine the multiple classifiers and further decision making. Several experiments were conducted to illustrate the performance of the proposed method using the UCI smartphone dataset, and the results show that the proposed method is more accurate than the state-of-art methods. © 2023 International Society of Information Fusion.

关键词： Frequency domain analysis

来源：评论

学校读者我要写书评

暂无评论

DSNet: A Superior Real-Time Semantic Segmentation Model for Road Scenes 9

DSNet: A Superior Real-Time Semantic Segmentation Model for ...

引用

9th International Conference on computer and Communications, ICCC 2023

作者： Yin, Zhenyu Shi, Xiaoqiang Zhang, Feiqing Xu, Guangyuan Qin, Li Li, Shurui Chinese Academy of Sciences Shenyang Institute of Computing Technology Shenyang China University of Chinese Academy of Sciences Shenyang China Liaoning Key Lab. of Domestic Industrial Control Platform Technology on Basic Hardware Software Shenyang China Shenyang Aerospace University School of Computer Science Shenyang China

ISBN: (纸本)9798350317251

A series of semantic segmentation models have achieved remarkable accuracy, but their high computational cost limits their practical applications in areas such as autonomous driving and robotics. Recently, some multi-branch real-time semantic segmentation models have been proposed to improve segmentation accuracy by introducing detail branches. However, there is a lack of auxiliary guidance in the design of detail branches, and there is a high computational cost problem in designing multi-branch information fusion modules. Therefore, to address these issues, in this paper, we propose a real-time semantic segmentation model called DSNet, which achieves a good balance between speed and accuracy. DSNet consists of two branches: the detail branch and the semantic branch. The detail branch effectively extracts detail information by introducing edge loss as auxiliary supervision, while the semantic branch extracts deeper-level semantic information by increasing network depth and channel count. Finally, the fusion of detail and semantic information serves as the feature for predicting the segmentation map. To fuse the detail and semantic information, we design a novel feature fusion module called LSAF, which efficiently integrates features from different branches with low computational costs. Our method achieves a speed of 152.3 FPS with an accuracy of 72.8% on the CityScapes test dataset. © 2023 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Tensor and Minimum Connected Dominating Set based Confident Information Coverage Reliability Evaluation for IoT

IEEE Transactions on Sustainable Computing

引用

IEEE Transactions on Sustainable Computing 2024年第03期10卷 547-561页

作者： Xiao, Ziheng Zhu, Chenlu Feng, Wei Liu, Shenghao Deng, Xianjun Lu, Hongwei Yang, Laurence T. Park, Jong Hyuk Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China Artificial Intelligence and Intelligent Transportation Joint Technical Center of HUST and Hubei Chutian Intelligent Transportation Company Ltd United States Network and Industrial Control Information Security Technology Department China Nuclear Power Operation Technology Company Ltd. 1011 Xiongchu Avenue Hubei Wuhan430070 China The Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul01811 Korea Republic of

Internet of Things (IoT) reliability evaluation contributes to the sustainable computing and enhanced stability of the network. Previous algorithms usually evaluate the reliability of IoT by enumenating the states of nodes and networks, which are difficult to handle IoT with hundreds of nodes because the computational cost. In this paper, a novel algorithm, TMCRA, is proposed to evaluate the reliability of IoT in complex network environment, which consider both coverage and connectivity. For coverage, TMCRA employs the Confident Information Coverage (CIC) model to divide the target area into independent grids and calculates the coverage rate. In terms of connectivity, TMCRA forming the Virtual Backbone Network (VBN) based on two proposed methods: TMA and MGIN, and evaluate connectivity by analyzing the VBN rather than the whole network. The TMA and MGIN are two algorithms for constructing Minimum Connected Dominant Sets (MCDS), which are suitable for different scale networks. Finally, based on the data of coverage and connectivity, TMCRA utilizes tensors for the unified modeling and representation of network structure, and calculates IoT reliability based on the tensors. Simulations are carried out for various sizes of IoT to show the advantages and effectiveness of the proposed approach in reliability evaluation. © 2016 IEEE.

关键词： Data reliability

来源：评论

学校读者我要写书评

暂无评论

Fractional Order Sliding Mode control with Fuzzy Parameter Tuning Applied to a SCARA Robot

Fractional Order Sliding Mode Control with Fuzzy Parameter T...

引用

Mechatronic Systems Supervision (IW_MSS), IEEE International Workshop on

作者： Aicha Znidi Fatma Abdelhedi Ahmed Said Nouri Nabil Derbel Lab: Numerical Control of Industrial Processes National Engineering School of Gabes University of Gabes Tunisia Department of Electrical and Computer Engineering College of Engineering King Abdulaziz University Jeddah Saudi Arabia Control & Energy Management Laboratory University of Sfax National Engineering School of Sfax Tunisia

ISBN: (数字)9798350378382

ISBN: (纸本)9798350378399

This paper presents the application of Fractional Order Sliding Mode control (FO-SMC) in order to achieve a robust motion trajectory regulation in dynamic robot systems. The proposed control strategy benefits of both advantages of fractional calculus and sliding mode control to upgrade the robustness and the performances of the controller. Moreover, the paper proposes to use a fuzzy tuning of sliding mode controller in order to satisfy the capabilities of the actuators. The stability of the closed loop system has been demonstrated using the Lyapunov theory. Simulation results demonstrate the efficiency of the proposed method achieving precise trajectory tracking and robust performances, it has been shown that fuzzy tuning of the sliding function parameters significantly reduces control variable peaks, making the control more suitable for actuator application.

关键词： Asymptotic stability Actuators Trajectory tracking Simulation Manipulators Stability analysis Closed loop systems Tuning Sliding mode control Fractional calculus

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：