检索结果-内蒙古大学图书馆

IEEE International Conference on Electrical Engineering and Photonics (EExPolytech)

作者： Mingyang Wang Tian Cao Shihan Chen Changyong Pan Jian Song Department of Electronic Engineering Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing China State Key Laboratory of Integrated Service Networks School of Telecommunications Engineering Xidian University Xian China Key Laboratory of Digital TV System of Guangdong Province and Shenzhen City Research Institute of Tsinghua University in Shenzhen Shenzhen China

Ultraviolet communication (UVC) has emerged as a promising solution for close-range communication within the intricate electromagnetic setting. The atmosphere's attenuation, however, restricts the scope and rate of communication. We demonstrated a line-of-sight (LOS) UV communication system. In our system, we employed ultraviolet light-emitting diodes (LEDs) in our system to transmit the signal light with a broad radiation angle and use lenses to enhance the communication range. We propose a combined approach of theory and practice to analyze the feasibility of a LOS UVC system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cramér-Rao Bound Minimization for a Passive Sensing Multi-ISAC system

引用

IEEE Transactions on Vehicular technology 2025年

作者： Chen, Jian Chen, Qikai Deng, Yansha Jia, Jie Yin, Baoxin Wang, Xingwei Northeastern University School of Computer Science and Engineering Shenyang110819 China Northeastern University Engineering Research Center of Security Technology of Complex Network System Ministry of Education Shenyang110819 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China King's College London LondonWC2R 2LS United Kingdom

The integrated sensing and communication (ISAC) system can simultaneously provide communication and radar sensing, effectively improving spectrum utilization. However, existing research mainly focuses on the mono-static sensing ISAC system, which has shortcomings in limited sensing range and accuracy. We thus investigate a passive sensing multi-ISAC system with multiple communication users and sensing targets, and consider two cases for multi-target sensing without and with prior target knowledge at the base stations (BSs), in which the BSs are interested in estimating the targets' response matrix and channel coefficients, respectively. We also formulate a joint beamforming problem to minimize the Cramér-Rao bound (CRB) of the worst estimation constrained by communication requirements, and obtain the optimal solution with semidefinite relaxation (SDR) assisted transformation. To verify the advantages of our proposed scheme, we consider the bi-static BSs system (B-B) and beamforming with sensing interference cancellation (W-S) as two benchmark schemes. Numerical results illustrate that the proposed scheme obtains better sensing performance and effectively alleviates the effect caused by sensing interference. © 1967-2012 IEEE.

关键词： Cramer-Rao bounds

来源：评论

学校读者我要写书评

暂无评论

LOG-LIO: A LiDAR-Inertial Odometry with Efficient Local Geometric Information Estimation

arXiv

引用

arXiv 2023年

作者： Huang, Kai Zhao, Junqiao Zhu, Zhongyang Ye, Chen Feng, Tiantian The School of Surveying and Geo-Informatics Tongji University Shanghai China Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The MOE Key Lab of Embedded System and Service Computing Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China

Local geometric information, i.e., normal and distribution of points, is crucial for LiDAR-based simultaneous localization and mapping (SLAM) because it provides constraints for data association, which further determines the direction of optimization and ultimately affects the accuracy of localization. However, estimating normal and distribution of points are time-consuming tasks even with the assistance of kdtree or volumetric maps. To achieve fast normal estimation, we look into the structure of LiDAR scan and propose a ring-based fast approximate least squares (Ring FALS) method. With the Ring structural information, estimating the normal requires only the range information of the points when a new scan arrives. To efficiently estimate the distribution of points, we extend the ikd-tree to manage the map in voxels and update the distribution of points in each voxel incrementally while maintaining its consistency with the normal estimation. We further fix the distribution after its convergence to balance the time consumption and the correctness of representation. Based on the extracted and maintained local geometric information, we devise a robust and accurate hierarchical data association scheme where point-to-surfel association is prioritized over point-to-plane. Extensive experiments on diverse public datasets demonstrate the advantages of our system compared to other state-of-the-art methods. Our open source implementation is available at https://***/tiev-tongji/LOG-LIO. Copyright © 2023, The Authors. All rights reserved.

关键词： Optical radar

来源：评论

学校读者我要写书评

暂无评论

LIMOT: A Tightly-Coupled system for LiDAR-Inertial Odometry and Multi-Object Tracking

arXiv

引用

arXiv 2023年

作者： Zhu, Zhongyang Zhao, Junqiao Huang, Kai Tian, Xuebo Lin, Jiaye Ye, Chen Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The MOE Key Lab of Embedded System and Service Computing Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China The School of Surveying and Geo-Informatics Tongji University Shanghai China

Simultaneous localization and mapping (SLAM) is critical to the implementation of autonomous driving. Most LiDAR-inertial SLAM algorithms assume a static environment, leading to unreliable localization in dynamic environments. Moreover, the accurate tracking of moving objects is of great significance for the control and planning of autonomous vehicles. This study proposes LIMOT, a tightly-coupled multi-object tracking and LiDAR-inertial odometry system that is capable of accurately estimating the poses of both ego-vehicle and objects. We propose a trajectory-based dynamic feature filtering method, which filters out features belonging to moving objects by leveraging tracking results before scan-matching. Factor graph-based optimization is then conducted to optimize the bias of the IMU and the poses of both the ego-vehicle and surrounding objects in a sliding window. Experiments conducted on the KITTI tracking dataset and self-collected dataset show that our method achieves better pose and tracking accuracy than our previous work DL-SLOT and other baseline methods. Our open-source implementation is available at https://***/tiev-tongji/LIMOT. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

The Mechanism of Mobile Communication technology Prompting Digital Transformation of Manufacturing Industry: From the Perspective of Data Factor Empowerment 24

The Mechanism of Mobile Communication Technology Prompting D...

引用

Proceedings of the 2024 10th International Conference on Communication and Information Processing

作者： Ran Li Muhua Wei Huili Liu Jiayin Qi Lina Liu Department of User and Market Research China Mobile Research Institute Beijing Beijing China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou Guangzhou China and Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing Beijing China School of Economics and Management Beijing University of Posts and Telecommunications Beijing Beijing China

ISBN: (纸本)9798400717444

Abstract: The digital transformation of manufacturing industry is a crucial measure for achieving high-quality development, and mobile communication technology plays a significant role in this process. This paper focuses on exploring the internal mechanism of mobile communication technology promoting the digital transformation of manufacturing industry, with a particular emphasis on three major technologies: 5G, 5G-A, and 6G. Firstly, the paper summarizes the latest progress of mobile communication technology in the field of manufacturing digital transformation. Secondly, it outlines the characteristics of technological evolution from 5G to 6G. Thirdly, based on the technological evolution process, it presents the three major capabilities of 6G, namely transmission, integrated sensing and communication, and intelligent computing. It further elaborates on how mobile communication technology gives rise to data facotor and clarifies the internal mechanism of mobile communication technology enabling data factor to empower the digital transformation of manufacturing industry. Finally, it looks forward to the typical development trends of 6G in the field of manufacturing digital transformation.

关键词： 5G

来源：评论

学校读者我要写书评

暂无评论

New Method of Traffic Flow Forecasting Based on QPSO Strategy for Internet of Vehicles 4

New Method of Traffic Flow Forecasting Based on QPSO Strateg...

引用

4th IEEE International Conference on Smart Internet of Things, SmartIoT 2020

作者： Zhang, De-Gan Du, Jing-Yu Zhang, Ting Fan, Hong-Rui Tianjin University of Technology Tianjin Key Lab of Intelligent Computing Novel Software Technology Tianjin300384 China Tianjin University of Technology Ministry of Education Key Laboratory of Computer Vision and System Tianjin China

ISBN: (纸本)9781728165141

We propose a new method of traffic flow forecasting based on quantum particle swarm optimization strategy (QPSO) for Internet of Vehicles (IOV). Establish a corresponding model based on the characteristics of the traffic flow data. The genetic simulated annealing method is applied to the quantum particle swarm method to obtain the optimized initial cluster center, and is applied to the parameter optimization of the radial basis neural network prediction model. The function approximation of radial basis neural network can be used to obtain the required data. In addition, in order to compare the performance of the methods, a comparison study with other related methods such as QPSO-RBF is also performed. Our method can reduce prediction errors and get better and more stable prediction results. © 2020 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Learning Sequence Descriptor based on Spatio-Temporal Attention for Visual Place Recognition

arXiv

引用

arXiv 2023年

作者： Zhao, Junqiao Zhang, Fenglin Cai, Yingfeng Tian, Gengxuan Mu, Wenjie Ye, Chen Feng, Tiantian Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The MOE Key Lab of Embedded System and Service Computing Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China School of Surveying and Geo-Informatics Tongji University Shanghai China

Visual Place Recognition (VPR) aims to retrieve frames from a geotagged database that are located at the same place as the query frame. To improve the robustness of VPR in perceptually aliasing scenarios, sequence-based VPR methods are proposed. These methods are either based on matching between frame sequences or extracting sequence descriptors for direct retrieval. However, the former is usually based on the assumption of constant velocity, which is difficult to hold in practice, and is computationally expensive and subject to sequence length. Although the latter overcomes these problems, existing sequence descriptors are constructed by aggregating features of multiple frames only, without interaction on temporal information, and thus cannot obtain descriptors with spatio-temporal discrimination. In this paper, we propose a sequence descriptor that effectively incorporates spatio-temporal information. Specifically, spatial attention within the same frame is utilized to learn spatial feature patterns, while attention in corresponding local regions of different frames is utilized to learn the persistence or change of features over time. We use a sliding window to control the temporal range of attention and use relative positional encoding to construct sequential relationships between different features. This allows our descriptors to capture the intrinsic dynamics in a sequence of frames. Comprehensive experiments on challenging benchmark datasets show that the proposed approach outperforms recent state-of-the-art methods. The code is available at https://***/tiev-tongji/Spatio-Temporal-SeqVPR. Copyright © 2023, The Authors. All rights reserved.

关键词： Query processing

来源：评论

学校读者我要写书评

暂无评论

Structure Enhanced Prototypical Alignment for Unsupervised Cross-Domain Node Classification

SSRN

引用

SSRN 2023年

作者： Liu, Meihan Zhang, Zhen Ma, Ning Gu, Ming Wang, Haishuai Zhou, Sheng Bu, Jiajun College of Computer Science Zhejiang University Hangzhou310027 China Zhejiang Provincial Key Laboratory of Service Robot Zhejiang University Hangzhou310027 China School of Software Technology Zhejiang University Ningbo315048 China School of Computing National University of Singapore 117417 Singapore

Graph Neural Networks (GNNs) have demonstrated remarkable success in graph node classification task. However, their performance heavily relies on the availability of high-quality labeled data, which can be time-consuming and labor-intensive to acquire for graph-structured data. Therefore, the task of transferring knowledge from a label-rich graph (source domain) to a completely unlabeled graph (target domain) becomes crucial. In this paper, we propose a novel unsupervised graph domain adaptation framework called Structure Enhanced Prototypical Alignment (SEPA), which aims to learn domain-invariant representations on non-IID (non-independent and identically distributed) data. Specifically, SEPA captures class-wise semantics by constructing a prototype-based graph and introduces an explicit domain discrepancy metric to align the source and target domains. The proposed SPEA framework is optimized in an end-to-end manner, which could be incorporated into various GNN architectures. Experimental results on several real-world datasets demonstrate that our proposed framework outperforms recent state-of-the-art baselines with different gains. © 2023, The Authors. All rights reserved.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Low-Rank Subspace Representation from Optimal Coded-Aperture for Unsupervised Classification of Hypersepctral Imagery

Low-Rank Subspace Representation from Optimal Coded-Aperture...

引用

IEEE International Conference on Image Processing

作者： Jianchen Zhu Tong Zhang Shengjie Zhao Key Laboratory of Embedded System and Service Computing Ministry of Education

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

This paper aims at developing a clustering approach with spectral images directly from the compressive measurements of coded aperture snapshot spectral imager (CASSI). Assuming that compressed measurements often lie approximately in low dimensional subspaces corresponding to multiple classes, state of the art methods generally obtains optimal solution for each step separately but cannot guarantee that it will achieve the globally optimal clustering results. In this paper, a low-rank subspace representation (LRSR) algorithm is proposed to perform clustering on the compressed measurements. In addition, a subspace structured norm is added into the objective of low-rank representation problem exploiting the fact that each point in a union of subspaces can be expressed as a sparse linear combination of all other points and that the matrix of the points within each subspace is low rank. Simulation with real dataset illustrates the accuracy of the proposed spectral image clustering approach.

关键词： Image coding Encoding Apertures Clustering algorithms Imaging Three-dimensional displays Sensors

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition Empowered Human-Computer Interaction with Domain Adaptation Network

引用

IEEE Transactions on Consumer Electronics 2024年

作者： Xu, Xu Fu, Chong Chen, Junxin Northeastern University School of Computer Science and Engineering Shenyang110004 China Dalian University of Technology China The School of Software Dalian116621 China Northeastern University School of Computer Science and Engineering Shenyang110004 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Ministry of Education Engineering Research Center of Security Technology of Complex Network System Shenyang110004 China Dalian University of Technology School of Software Dalian116621 China

Multi-modal emotion recognition plays a vital role in the human-computer interaction (HCI) for consumer electronics. Nowadays, many studies have developed multi-modal fusion algorithms for this ***, two challenging issues remain unsolved, i.e., inefficient multi-modal feature fusion and unclear distance in feature *** this end, we develop a novel framework, namely LAFDA-Net, for cross-subject emotion recognition using EEG and eye movement *** is based on low-rank fusion and domain adaptation *** specifically, the multi-modal signals are input into the feature extraction branch in parallel to generate ***, these features are fused by the low-rank fusion branch, reducing complexity and avoiding ***, the fused features are flattened and sent to the classification branch to determine the emotion *** training, these features are input into the domain adaptive branch to bridge the gap between the source domain and target *** benchmark datasets, i.e., SEED, SEED-IV, and SEED-V, are employed for performance *** results demonstrate that the proposed LAFDA-Net is robust, effective, and has advantages over peer methods. © 1975-2011 IEEE.

关键词： Emotion Recognition

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：