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AR assistance for efficient dynamic target search

Computational Visual Media 2023年第1期9卷 177-194页

作者： Zixiang Zhao Jian Wu Lili Wang State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina

When searching for a dynamic target in an unknown real world scene,search efficiency is greatly reduced if users lack information about the spatial structure of the *** target search studies,especially in robotics,focus on determining either the shortest path when the target’s position is known,or a strategy to find the target as quickly as possible when the target’s position is ***,the target’s position is often known intermittently in the real world,e.g.,in the case of using surveillance *** goal is to help user find a dynamic target efficiently in the real world when the target’s position is intermittently *** order to achieve this purpose,we have designed an AR guidance assistance system to provide optimal current directional guidance to users,based on searching a prediction *** assume that a certain number of depth cameras are fixed in a real scene to obtain dynamic target’s *** system automatically analyzes all possible meetings between the user and the target,and generates optimal directional guidance to help the user catch up with the target.A user study was used to evaluate our method,and its results showed that compared to free search and a top-view method,our method significantly improves target search efficiency.

关键词： augmented reality(AR) search guidance

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Sparsity-based efficient simulation of cluster targets electromagnetic scattering

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Journal of Systems engineering and Electronics 2023年第2期34卷 299-306页

作者： TIAN Yuguang LIU Yixin CHEN Xuan CHEN Penghui WANG Jun CHEN Junwen Communication University of China Beijing 100024China School of Electronic and Information Engineering Beihang UniversityBeijing 100191China Science and Technology on Electromagnetic Scattering Laboratory Beijing 100854China

An efficient and real-time simulation method is proposed for the dynamic electromagnetic characteristics of cluster targets to meet the requirements of engineering practical ***,the coordinate transformation method is used to establish a geometric model of the observation scene,which is described by the azimuth angles and elevation angles of the radar in the target reference frame and the attitude angles of the target in the radar reference ***,an approach for dynamic electromagnetic scattering simulation is ***,a fast-computing method based on sparsity in the time domain,space domain,and frequency domain is *** method analyzes the sparsity-based dynamic scattering characteristic of the typical cluster *** error between the sparsity-based method and the benchmark is small,proving the effectiveness of the proposed method.

关键词： geometric model of the observation scene dynamic electromagnetic scattering simulation sparsity-based method

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FAME: Towards Factual Multi-Task Model Editing

FAME: Towards Factual Multi-Task Model Editing

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Zeng, Li Shan, Yingyu Liu, Zeming Yao, Jiashu Guo, Yuhang School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9798891761643

Large language models (LLMs) embed extensive knowledge and utilize it to perform exceptionally well across various tasks. Nevertheless, outdated knowledge or factual errors within LLMs can lead to misleading or incorrect responses, causing significant issues in practical applications. To rectify the fatal flaw without the necessity for costly model retraining, various model editing approaches have been proposed to correct inaccurate knowledge within LLMs in a cost-efficient way. To evaluate these model editing methods, previous work introduced a series of datasets. However, most of the previous datasets only contain fabricated data in a single format, which diverges from real-world model editing scenarios, raising doubts about their usability in practice. To facilitate the application of model editing in real-world scenarios, we propose the challenge of practicality. To resolve such challenges and effectively enhance the capabilities of LLMs, we present FAME, an factual, comprehensive, and multi-task dataset, which is designed to enhance the practicality of model editing. We then propose SKEME, a model editing method that uses a novel caching mechanism to ensure synchronization with the real world. The experiments demonstrate that SKEME performs excellently across various tasks and scenarios, confirming its practicality. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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TED-EL: A Corpus for Speech Entity Linking 30

TED-EL: A Corpus for Speech Entity Linking

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Li, Silin Song, Ruoyu Lan, Tianwei Liu, Zeming Guo, Yuhang School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9782493814104

Speech entity linking amis to recognize mentions from speech and link them to entities in knowledge bases. Previous work on entity linking mainly focuses on visual context and text context. In contrast, speech entity linking focuses on audio context. In this paper, we first propose the speech entity linking task. To facilitate the study of this task, we propose the first speech entity linking dataset, TED-EL. Our corpus is a high-quality, human-annotated, audio, text, and mention-entity pair parallel dataset derived from technology, Entertainment, Design (TED) talks and includes a wide range of entity types (24 types). Based on TED-EL, we designed two types of models: ranking-based and generative speech entity linking models. We conducted experiments on the TED-EL dataset for both types of models. The results show that our ranking-based models outperform the generative models, achieving an F1 score of 60.68%. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Entity Linking Speech Entity Linking TED-EL

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UKF‐MOT:An unscented Kalman filter‐based 3D multi‐object tracker

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CAAI Transactions on Intelligence technology 2024年第4期9卷 1031-1041页

作者： Meng Liu Jianwei Niu Yu Liu Collective Intelligence&Collaboration Laboratory China North Artificial Intelligence and Innovation Research InstituteBeijingChina China North Vehicle Research Institute BeijingChina State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina School of Computer Science and Engineering Beihang UniversityBeijingChina

Multi‐object tracking in autonomous driving is a non‐linear *** better address the tracking problem,this paper leveraged an unscented Kalman filter to predict the object's *** the association stage,the Mahalanobis distance was employed as an affinity metric,and a Non‐minimum Suppression method was designed for *** the detections fed into the tracker and continuous‘predicting‐matching’steps,the states of each object at different time steps were described as their own continuous *** conducted extensive experiments to evaluate tracking accuracy on three challenging datasets(KITTI,nuScenes and Waymo).The experimental results demon-strated that our method effectively achieved multi‐object tracking with satisfactory ac-curacy and real‐time efficiency.

关键词： autonomous vehicle transportation

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Adaptive Interference Detection and Removal in SAR Images Based on the Order-2 Tracy-Widom Distribution 2

Adaptive Interference Detection and Removal in SAR Images Ba...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Yang, Huizhang Chen, Chengzhi Xi, Feng Lang, Ping Yin, Junjun Yang, Jian Nanjing University of Science and Technology Department of Electronic Engineering Nanjing China Tsinghua University Department of Electronic Engineering Beijing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798331515669

This paper proposes a novel eigenvalue-based detector for adaptive detection of radio interference in synthetic aperture radar (SAR) images. The proposed method leverages the increased eigenvalues caused by interference in single-look-complex SAR image blocks, where the interference is expected to have a small set of eigenvalues, particularly with a dominating one. Specifically, the method segments the image into multiple blocks, computes the eigenvalues of each block's covariance matrix, and compares the largest eigenvalue with a threshold to determine the presence of interference under the criteria of constant false alarm rate. The threshold is determined by the order-2 Tracy-Widom distribution of the largest eigenvalue for each image block under the assumption of image homogeneity. The proposed detector is integrated with our previously proposed block subspace filter for adaptive interference detection and removal. Experimental results on Sentinel-1 double-polarization and Gaofen-3 HV-polarization images demonstrate the effectiveness of the proposed method on adaptive detection and suppression of interference artefacts in SAR images. © 2024 IEEE.

关键词： Eigenvalues and eigenfunctions

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Shape Prior Enhanced Unet Model for Medical Image Segmentation

Shape Prior Enhanced Unet Model for Medical Image Segmentati...

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2024 IEEE International Conference on communications, Computing, Cybersecurity and Informatics, CCCI 2024

作者： Fang, Song Wang, Jiamin Zhao, Zirun Wei, Chaopeng Zhang, Xudong Wang, Jiaxin Obaidat, Mohammad S. Wang, Xiaokun School of Computer & Communication Engineering University of Science and Technology Beijing Beijing China King Abdullah II School of Information Technology University of Jordan Amman Jordan

ISBN: (纸本)9798350349832

Medical image segmentation is a critical and challenging task in modern medicine. This task faces issues such as low contrast between the target structures and surrounding tissues, as well as uncertainties in the morphology and location of pathological tissues. These challenges often result in the suboptimal performance of traditional segmentation methods, especially when dealing with complex structures. To address these issues, we propose a UNet model integrated with shape priors. This model utilizes a Shape Prior Module (SPM) to generate and update shape knowledge, which is then integrated as feature maps into the skip connections of the U-shaped network. By combining global and local information, the SPM enhances the network's comprehensive understanding of the image. Additionally, this module can be seamlessly integrated with the convolutional neural network architecture, enhancing the model's practicality and generalization capabilities. Moreover, we design a comprehensive loss function that integrates Dice, CE, and BoundaryDoU metrics, significantly improving the efficiency of model parameter optimization and learning. Experimental results on two medical image datasets demonstrate that the proposed shape prior network model yields better outcomes in enhancing segmentation accuracy and improving classification detection precision. © 2024 IEEE.

关键词： Convolutional neural networks

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Study on Robot Grasping System of SSVEP-BCI Based on Augmented Reality Stimulus

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Tsinghua science and technology 2023年第2期28卷 322-329页

作者： Shangen Zhang Yuanfang Chen Lijian Zhang Xiaorong Gao Xiaogang Chen School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Beijing Institute of Mechanical Equipment Beijing 100854China Department of Biomedical Engineering School of MedicineTsinghua UniversityBeijing100084China Institute of Biomedical Engineering Chinese Academy of Medical Sciences and Peking Union Medical CollegeTianjin 300192China

Although notable progress has been made in the study of Steady-State Visual Evoked Potential(SSVEP)-based Brain-computer Interface(BCI),several factors that limit the practical applications of BCIs still *** of these factors is the importability of the *** this study,Augmented Reality(AR)technology was introduced to present the visual stimuli of SSVEP-BCI,while the robot grasping experiment was designed to verify the applicability of the AR-BCI *** offline experiment was designed to determine the best stimulus time,while the online experiment was used to complete the robot grasping *** offline experiment revealed that better information transfer rate performance could be achieved when the stimulation time is 2 *** of the online experiment indicate that all 12 subjects could control the robot to complete the robot grasping task,which indicates the applicability of the AR-SSVEP-humanoid robot(NAO)*** study verified the reliability of the AR-BCI system and indicated the applicability of the AR-SSVEP-NAO system in robot grasping tasks.

关键词： Steady-State Visual Evoked Potential(SSVEP) Brain-computer Interface(BCI) Augmented Reality(AR) robot grasping system

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Modeling Super-Lightweight Cellular Traffic Prediction via Multiservice and Multimodal Feature Fusion Network

IEEE Networking Letters

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IEEE Networking Letters 2024年第1期6卷 16-20页

作者： Li, Yingqi Hao, Mingxiang Sun, Xiaochuan Zhang, Haijun University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China North China University of Science and Technology College of Artificial Intelligence Tangshan063210 China Hebei Key Laboratory of Industrial Perception Tangshan063210 China

Cellular Traffic Prediction has proven to be a key enabler towards automatic network management. However, to pursue performance improvement, the existing studies mainly focus on developing complex deep neural network models, which suffer from extensive computation cost and large model size inevitably. Such models are quite difficult to be deployed on resource-constrained devices. In this letter, we propose a multiservice and multimodal feature fusion network for super-lightweight cellular network traffic prediction, namely m^2FFNet , to address the issue. Briefly speaking, such a network consists of a duel feature extraction channel based on grouped 3D convolution for capturing multiservice feature and multimodal feature (yielded from wavelet transform decomposition), respectively. Simulation results demonstrate that our proposal can achieve comparable prediction accuracy as the state-of-the-art deep learning methods, meanwhile obtaining much less computation burden with rather few model size. © 2019 IEEE.

关键词： Feature extraction

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Blockchain-Based Trust Model for Inter-Domain Routing

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computers, Materials & Continua 2025年第3期82卷 4821-4839页

作者： Qiong Yang Li Ma Sami Ullah Shanshan Tu Hisham Alasmary Muhammad Waqas Faculty of Information Technology Beijing University of TechnologyBeijing100124China School of Information Science and Technology North China University of TechnologyBeijing100144China Department of Computer Science Shaheed Benazir Bhutto UniversitySheringal18050Pakistan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia School of Computing andMathematical Sciences Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUK School of Engineering Edith Cowan UniversityPerthWA 6027Australia

Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,communicating in a distributed dynamic environment,face several security challenges,with trust being one of the most important issues in inter-domain *** research,which performs trust evaluation when exchanging routing information to suppress malicious routing behavior,cannot meet the scalability requirements of BGP *** this paper,we propose a blockchain-based trust model for inter-domain *** model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the *** BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective *** incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing *** forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing *** use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust *** with the classical trust model,our trust model not only saves more storage overhead,but also provides higher security,especially reducing the impact of collusion attacks.

关键词： Inter-domain routing BGP security blockchain trust model trust mechanisms trust evaluation

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