检索结果-内蒙古大学图书馆

Versatile Tasks on Integrated Aerial Platforms Using Only Onboard Sensors: Control, Estimation, and Validation

IEEE Transactions on Robotics 2025年 41卷 3518-3538页

作者： Wang, Kaidi Lai, Ganghua Yu, Yushu Du, Jianrui Sun, Jiali Xu, Bin Franchi, Antonio Sun, Fuchun Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beijing Institute of Technology School of Mechanical Engineering Beijing100081 China University of Twente Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics and Computer Science Enschede7500 AE Netherlands Tsinghua University Department of Computer Science and Technology China

Connecting multiple aerial vehicles to a rigid central platform through passive spherical joints holds the potential to construct a fully-actuated aerial platform. The integration of multiple vehicles enhances efficiency in tasks like mapping and object reconnaissance. This paper proposes a control and state estimation framework for the Integrated Aerial Platform (IAP), enabling it to perform versatile tasks like object reconnaissance and physical interactive tasks with only onboard sensors. In the framework, the 6D motion control serves as the low-level controller, while the high-level controller comprises a 6D admittance filter and a perception-aware attitude correction module. The 6D admittance filter, serving as the interaction controller, is adaptable for aerial interaction tasks. The perception-aware attitude correction algorithm is carefully designed by adopting a geometric Model Predictive Controller (MPC). This algorithm, incorporating both offline and online calculations, proves to be well-suited for the intricate dynamics of an IAP. A 6D direct wrench controller is also developed for the IAP. Notably, both the interaction controller and the direct wrench controller operate without reliance on force/torque sensors. Instead, a wrench observer algorithm is devised, considering external disturbances. Additionally, based on the kinematics constraints of the multiple aerials in the platform, a fusion algorithm for multiple Visual-Inertial Odometry (VIO) and kinematics constraints is developed, providing more accurate localization. A prototype of the IAP is constructed, and its capabilities are demonstrated through experiments including perception-aware object reconnaissance, aerial mapping, aerial peg-in-hole task, and 6D contact wrench generation. All experiments are conducted exclusively with onboard sensors. These tasks exemplify the merits of the proposed IAP and validate the effectiveness of the proposed control framework and fusion algorithm. © 2004-2012

关键词： State estimation

来源：评论

学校读者我要写书评

暂无评论

Joint Watermarking and Encryption for Social Image Sharing

引用

computers, Materials & Continua 2025年第5期83卷 2927-2946页

作者： Conghuan Ye Shenglong Tan Shi Li Jun Wang Qiankun Zuo Bing Xiong School of Information Engineering Hubei University of EconomicsWuhan430205China School of Computer and Communication Engineering Changsha University of Science&TechnologyChangsha410114China

With the fast development of multimedia social platforms,content dissemination on social media platforms is becomingmore *** image sharing can also raise privacy *** encryption can protect social ***,most existing image protection methods cannot be applied to multimedia social platforms because of encryption in the spatial *** this work,the authors propose a secure social image-sharing method with watermarking/fingerprinting and ***,the fingerprint code with a hierarchical community structure is designed based on social network ***,discrete wavelet transform(DWT)from block discrete cosine transform(DCT)directly is *** that,all codeword segments are embedded into the LL,LH,and HL subbands,*** selected subbands are confused based on Game of Life(GoL),and then all subbands are diffused with singular value decomposition(SVD).Experimental results and security analysis demonstrate the security,invisibility,and robustness of our ***,the superiority of the technique is elaborated through comparison with some related image security *** solution not only performs the fast transformation from block DCT to one-level DWT but also protects users’privacy in multimedia social *** the proposed method,JPEG image secure sharing in multimedia social platforms can be ensured.

关键词： Multimedia security digital watermarking image encryption image sharing privacy protection

来源：评论

学校读者我要写书评

暂无评论

Latency minimization for multiuser computation offloading in fog-radio access networks

引用

Digital communications and Networks 2025年第1期11卷 160-171页

作者： Wei Zhang Shafei Wang Ye Pan Qiang Li Jingran Lin Xiaoxiao Wu School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu611731China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089China

Recently,the Fog-Radio Access Network(F-RAN)has gained considerable attention,because of its flexible architecture that allows rapid response to user *** this paper,computational offloading in F-RAN is considered,where multiple User Equipments(UEs)offload their computational tasks to the F-RAN through fog *** UE can select one of the fog nodes to offload its task,and each fog node may serve multiple *** tasks are computed by the fog nodes or further offloaded to the cloud via a capacity-limited fronhaul *** order to compute all UEs'tasks quickly,joint optimization of UE-Fog association,radio and computation resources of F-RAN is proposed to minimize the maximum latency of all *** min-max problem is formulated as a Mixed Integer Nonlinear Program(MINP).To tackle it,first,MINP is reformulated as a continuous optimization problem,and then the Majorization Minimization(MM)method is used to find a *** MM approach that we develop is unconventional in that each MM subproblem is solved inexactly with the same provable convergence guarantee as the exact MM,thereby reducing the complexity of MM *** addition,a cooperative offloading model is considered,where the fog nodes compress-and-forward their received signals to the *** this model,a similar min-max latency optimization problem is formulated and tackled by the inexact *** results show that the proposed algorithms outperform some offloading strategies,and that the cooperative offloading can exploit transmission diversity better than noncooperative offloading to achieve better latency performance.

关键词： Fog-radio access network Fog computing Majorization minimization WMMSE

来源：评论

学校读者我要写书评

暂无评论

ET-Net:A Novel Framework for Fine-Grained Traffic Classification in Intelligent Vehicle Applications

引用

China communications 2025年第1期22卷 265-276页

作者： Wei Wenjie Ji Nan Gao Feiran Lin Fuhong School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China China Communications Magazine Co.LTD Beijing 100081China Beijing-Dublin International College Beijing University of TechnologyBeijing 100124China North China Electric Power University Beijing 102206China

Intelligent vehicle applications provide convenience but raise privacy and security *** of sensitive data,including vehicle location,and facial recognition information,poses a threat to user ***,traffic classification is vital for promptly overseeing and controlling applications with sensitive *** this paper,we propose ETNet,a framework that combines multiple features and leverages self-attention mechanisms to learn deep relationships between ***-Net employs a multisimilarity triplet network to extract features from raw bytes,and exploits self-attention to capture long-range dependencies within packets in a session and contextual information ***,we utilizing the loss function to more effectively integrate information acquired from both byte sequences and their corresponding *** simulated evaluations on datasets with similar attributes,ET-Net demonstrates the ability to finely distinguish between nine categories of applications,achieving superior results compared to existing methods.

关键词： attention mechanism encrypted traffic classification intelligent vehicles privacy and security

来源：评论

学校读者我要写书评

暂无评论

TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding

TROI: Cross-Subject Pretraining with Sparse Voxel Selection ...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Wang, Ziyu Pan, Tengyu Li, Zhenyu Wu, Ji Li, Xiuxing Wang, Jianyong Department of Computer Science and Technology Tsinghua University Beijing China School of Computer Science and Engineering Beihang University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9798350368741

fMRI (functional Magnetic Resonance Imaging) visual decoding involves decoding the original image from brain signals elicited by visual stimuli. This often relies on manually labeled ROIs (Regions of Interest) to select brain voxels. However, these ROIs can contain redundant information and noise, reducing decoding performance. Additionally, the lack of automated ROI labeling methods hinders the practical application of fMRI visual decoding technology, especially for new subjects. This work presents TROI (Trainable Region of Interest), a novel two-stage, data-driven ROI labeling method for cross-subject fMRI decoding tasks, particularly when subject samples are limited. TROI leverages labeled ROIs in the dataset to pretrain an image decoding backbone on a cross-subject dataset, enabling efficient optimization of the input layer for new subjects without retraining the entire model from scratch. In the first stage, we introduce a voxel selection method that combines sparse mask training and low-pass filtering to quickly generate the voxel mask and determine input layer dimensions. In the second stage, we apply a learning rate rewinding strategy to fine-tune the input layer for downstream tasks. Experimental results on the same small sample dataset as the baseline method for brain visual retrieval and reconstruction tasks show that our voxel selection method surpasses the state-of-the-art method MindEye2 with an annotated ROI mask. © 2025 IEEE.

关键词： Computational neuroscience multi-modal learning region of interest analysis small sample learning

来源：评论

学校读者我要写书评

暂无评论

ACbot:an IIoT platform for industrial robots

引用

Frontiers of computer science 2025年第4期19卷 13-27页

作者： Rui WANG Xudong MOU Tianyu WO Mingyang ZHANG Yuxin LIU Tiejun WANG Pin LIU Jihong YAN Xudong LIU School of Computer Science and Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100194China School of Software Beihang UniversityBeijing 100191China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Engineering China University of GeosciencesBeijing 100083China

As the application of Industrial Robots(IRs)scales and related participants increase,the demands for intelligent Operation and Maintenance(O&M)and multi-tenant collaboration *** methods could no longer cover the requirements,while the Industrial Internet of Things(IIoT)has been considered a promising ***,there’s a lack of IIoT platforms dedicated to IR O&M,including IR maintenance,process optimization,and knowledge *** this context,this paper puts forward the multi-tenant-oriented ACbot platform,which attempts to provide the first holistic IIoT-based solution for O&M of *** on an information model designed for the IR field,ACbot has implemented an application architecture with resource and microservice management across the cloud and multiple *** this basis,we develop four vital applications including real-time monitoring,health management,process optimization,and knowledge *** have deployed the ACbot platform in real-world scenarios that contain various participants,types of IRs,and *** date,ACbot has been accessed by 10 organizations and managed 60 industrial robots,demonstrating that the platform fulfills our ***,the application results also showcase its robustness,versatility,and adaptability for developing and hosting intelligent robot applications.

关键词： IIoT platform industrial robots cloud-edge collaboration intelligent applications

来源：评论

学校读者我要写书评

暂无评论

Improving Micro-expression Recognition using Multi-sequence Driven Face Generation

Improving Micro-expression Recognition using Multi-sequence ...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Chen, Yuan Zhong, Chongju Huang, Pinyi Cai, Wangyang Wang, Lei School of Computer Science and Engineering Central South University China School of Computer and Communication Engineering Changsha University of Science and Technology China

ISBN: (纸本)9798350368741

Micro-expression (ME) recognition holds great potential for revealing true human emotions. A significant barrier to effective ME recognition is the lack of sufficient annotated ME video data because MEs are subtle and involuntary facial expressions that are very hard to capture. To address this issue, data augmentation techniques, such as ME migration based on a driven video, have been employed to enrich training samples. Considering that MEs can be complex facial movements involving multiple action unit (AU) changes, we propose a novel ME generation approach that enables the creation of more realistic facial sequences by fusing MEs from multiple videos rather than just single driven video. To enhance the effectiveness of multi-sequence ME transfer, we adapt the thin plate spline motion model and improve traditional face alignment methods to better suit the model, facilitating multi-sequence driven ME generation. In our experiments, we conduct a downstream ME recognition task using models trained on our augmented ME sequences to demonstrate the effectiveness of our approach on the SAMM, SMIC, and CASME II datasets. The results confirm that our proposed approach outperforms state-of-the-art (SOTA) augmentation and generation methods in terms of F1 score and recognition accuracy. © 2025 IEEE.

关键词： face alignment micro-expression generation thin plate spline motion model video fusion

来源：评论

学校读者我要写书评

暂无评论

Global Navigation Satellite System Reflectometry specular point positioning method based on reflection geometric model: Suitable for land and ocean applications

引用

Journal of Applied Remote Sensing 2025年第1期19卷

作者： Li, Shuaishuai He, Shanbao Cheng, Xing Wang, Feng Xie, Heng Pang, Jingjing Cai, Min Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing China Beihang University School of Electronic and Information Engineering Beijing China Beijing Information Science and Technology University School of Information and Communication Engineering Beijing China

The accurate positioning of the specular point of the spaceborne global navigation satellite system reflectometry (GNSS-R) receiver is a key step in using GNSS-R technology for geophysical parameter retrieval. As GNSS-R applications expand across diverse environments ranging from land and oceans to glaciers, traditional geometric positioning accuracy is no longer sufficient to meet the demands of these varied applications. Specifically, positioning algorithms must not only facilitate real-time spaceborne processing but also adapt to fluctuating surface conditions, all while sustaining high levels of accuracy and efficiency. In response to these demands, we propose a positioning algorithm tailored for spaceborne GNSS-R specular points across various surface environments. The proposed algorithm integrates actual surface height data by leveraging surface models for localized terrain fitting. It employs a regional grid traversal method, guided by geographic positioning criteria, to accurately search for specular points that satisfy specific conditions. Considering the impact of initial position accuracy on traversal speed, we developed an ellipsoidal reflection geometric model based on the unique properties of the ellipsoid. This model facilitates the swift, non-iterative determination of a high-precision initial position for specular points. Experimental data indicate that our proposed approach reduces the Euclidean distance error of the initial position by ~87.5% and enhances grid traversal efficiency by a factor of more than eight times. To verify the robustness of the proposed method, this paper conducted multiple experiments in both ocean and land scenarios, including case studies in the Qinghai-Tibet Plateau region. The findings highlight that the normal vector angle analysis criterion offers superior reliability in complex terrains, positioning it as the optimal criterion for the positioning of specular points. © 2025 Society of Photo-Optical Instrumentation Engi

关键词： Global positioning system

来源：评论

学校读者我要写书评

暂无评论

Research on Intelligent Signal Detection in the Internet of Things Based on Deep Learning Algorithms 24

Research on Intelligent Signal Detection in the Internet of ...

引用

3rd International Conference on Algorithms, Data Mining, and Information technology, ADMIT 2024

作者： Liu, Xingcen School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9798400718120

With the rapid development of Internet of Things technology, intelligent signal detection has become a highly challenging key issue. Traditional manual feature extraction methods are no longer able to cope with complex and ever-changing practical environments. In response to this issue, this study proposes an intelligent signal detection model for the Internet of Things based on deep learning. This model adopts a convolutional neural network structure, which can automatically learn local pattern features in signals, thereby improving its adaptability to complex environments. Research a large-scale wireless signal dataset constructed based on real IoT scenarios, and adopt reasonable data preprocessing and augmentation strategies. Through scientific model training and multi-dimensional evaluation index settings, a comprehensive evaluation of the proposed model was conducted on the test set. The experimental results show that the model has achieved excellent performance over traditional methods in key indicators such as accuracy, recall, and F1 score, especially in complex signal recognition scenarios. © 2024 Copyright held by the owner/author(s).

关键词： Deep learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Frequency-enhanced and decomposed transformer for multivariate time series anomaly detection

引用

Applied Intelligence 2025年第6期55卷 1-18页

作者： Li, Shijiang Wang, Zhihai Wang, Xiaokang Yin, Zihao Yao, Muyun School of Computer Science and Technology Beijing Jiaotong University Beijing China School of Automation and Intelligence Beijing Jiaotong University Beijing China Engineering Center on Computer Network Management in Hi-Speed Railway Ministry of Education Beijing Jiaotong University Beijing China

With the widespread adoption of the Internet of Things (IoT), vast amounts of multivariate time series data are generated, which reflect the operational status of systems. Accurate and efficient anomaly detection in these data is crucial for maintaining system stability. However, data from unstable environments often exhibit high volatility, data drift, and complex patterns of anomalies. Unsupervised anomaly detection models are typically designed for stable data and lack generalizability, leading to a high rate of false positives when applied to unstable data. This paper introduces the frequency-enhanced and decomposed transformer for anomaly detection (FDTAD), which is a novel anomaly detection model based on a transformer that is enhanced with frequency and time series decomposition. FDTAD addresses data drift by decomposing time series and leverages both time-domain and frequency-domain information to improve the generalization ability of the model. The model preserves major amplitudes in the frequency domain to extract primary periodic patterns, uses spectral residuals to capture detailed variations, and incorporates a frequency-domain correlation attention mechanism to extract dependencies in frequency-domain data in a sparse representation. Additionally, a spatiotemporal module is designed to extract the temporal correlations in the data and spatial correlations among the data with different attributes. FDTAD combines a data periodic pattern reconstructor and a data detailed pattern reconstructor through an adversarial mechanism to achieve maximum accuracy in reconstructing normal data. Extensive experiments on 10 public datasets demonstrate that FDTAD outperforms state-of-the-art baseline methods, with a 4.1% improvement in the F1 score and a 4.7% improvement in precision. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Time series

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：