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检索条件"机构=State Key Laboratory Software Engineering and School Computer and Complex Network Research Center"
540 条 记 录,以下是181-190 订阅
排序:
Near-field communications:characteristics,technologies,and engineering
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Frontiers of Information Technology & Electronic engineering 2024年 第12期25卷 1580-1626页
作者: Yajun ZHAO Linglong DAI Jianhua ZHANG Ran JI Mengnan JIAN Hao XUE Hongkang YU Yunqi SUN Yu LU Zidong WU Zhuo XU Jinke LI Haiyang MIAO Zhiqiang YUAN Pan TANG Jiayu SHEN Tierui GONG Haixia LIU Jiaqi HAN Qiang FENG Zhi CHEN Lingxiang LI Gang YANG Yong ZENG Cunhua PAN Wang LIU Kangda ZHI Weidong HU Yuanwei LIU Xidong MU Chau YUEN Mérouane DEBBAH Chongwen HUANG Long LI Ping ZHANG State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518055China ZTE Corporation Beijing 100192China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310007China Key Laboratory of High Speed Circuit Design and EMC of Ministry of Education School of Electronic EngineeringXidian UniversityXi’an 710071China Collaborative Innovation Center of Information Sensing and Understanding Xidian UniversityXi’an 710071China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of ChinaChengdu 611731China National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211111China School of Electrical Engineering and Computer Science Technical University of BerlinBerlin 10623Germany School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Centre for Wireless Innovation(CWI) School of ElectronicsElectrical Engineering and Computer ScienceQueen’s University BelfastBelfast BT39DTUK School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore KU 6G Research Center Khalifa University of Science and TechnologyAbu DhabiUnited Arab Emirates
Near-field technology is increasingly recognized due to its transformative potential in communication systems,establishing it as a critical enabler for sixth-generation(6G)telecommunication *** paper presents a compre... 详细信息
来源: 评论
A Phase Estimation Algorithm for Quantum Speed-Up Multi-Party Computing
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computers, Materials & Continua 2021年 第4期67卷 241-252页
作者: Wenbin Yu Hao Feng Yinsong Xu Na Yin Yadang Chen Zhi-Xin Yang Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Jiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Department of Computer Science and Engineering Michigan State UniversityEast Lansing48824MIUSA State Key Laboratory of Internet of Things for Smart City and Department of Electromechanical Engineering University of Macao999078Macao
Security and privacy issues have attracted the attention of researchers in the field of IoT as the information processing scale grows in sensor *** computing,theoretically known as an absolutely secure way to store an... 详细信息
来源: 评论
FedABC: Targeting Fair Competition in Personalized Federated Learning
arXiv
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arXiv 2023年
作者: Wang, Dui Shen, Li Luo, Yong Hu, Han Su, Kehua Wen, Yonggang Tao, Dacheng National Engineering Research Center for Multimedia Software School of Computer Science Institute of Artificial Intelligence Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University China Hubei Luojia Laboratory Wuhan China JD Explore Academy China School of Information and Electronics Beijing Institute of Technology China School of Computer Science and Engineering Nanyang Technological University Singapore
Federated learning aims to collaboratively train models without accessing their client’s local private data. The data may be Non-IID for different clients and thus resulting in poor performance. Recently, personalize... 详细信息
来源: 评论
DRL-Based Optimization for AoI and Energy Consumption in C-V2X Enabled IoV
IEEE Transactions on Green Communications and Networking
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IEEE Transactions on Green Communications and networking 2025年
作者: Zhang, Zheng Wu, Qiong Fan, Pingyi Cheng, Nan Chen, Wen Letaief, Khaled B. Jiangnan University School of Internet of Things Engineering Wuxi214122 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering State Key laboratory of Space Network and Communications Tsinghua University Beijing100084 China Xidian University State Key Lab. of ISN School of Telecom-munications Engineering Xi'an710071 China Shanghai Jiao Tong University Department of Electronic Engineering Shanghai200240 China Department of Electrical and Computer Engineer-ing Hong Kong
To address communication latency issues, the Third Generation Partnership Project (3GPP) has defined Cellular-Vehicle to Everything (C-V2X) technology, which includes Vehicle-to-Vehicle (V2V) communication for direct ... 详细信息
来源: 评论
Cross-Modal Few-Shot Learning: a Generative Transfer Learning Framework
arXiv
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arXiv 2024年
作者: Yang, Zhengwei Li, Yuke Sun, Qiang Fernando, Basura Huang, Heng Wang, Zheng National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence School of Computer Science Wuhan University China Hubei Key Laboratory of Multimedia and Network Communication Engineering China Centre for Frontier AI Research Agency for Science Technology and Research Singapore University of Maryland College Park United States University of Toronto Canada MBZUAI United Arab Emirates
Most existing studies on few-shot learning focus on unimodal settings, where models are trained to generalize to unseen data using a limited amount of labeled examples from a single modality. However, real-world data ... 详细信息
来源: 评论
research on key Word Information Retrieval Based on Inverted Index  8th
Research on Key Word Information Retrieval Based on Inverted...
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8th International Conference on Artificial Intelligence and Security , ICAIS 2022
作者: Qi, Meihan Fang, Wei Zhao, Yongming Sha, Yu Sheng, Victor S. School of Computer and Software Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing210044 China State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing100081 China China Meteorological Administration Training Center Beijing China Department of Computer Texas Tech University LubbockTX79409 United States
With the advent of the era of big data, data has penetrated into every aspect of social life and become an important production factor in various industries. However, while providing convenience to our life, massive i... 详细信息
来源: 评论
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
arXiv
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arXiv 2024年
作者: Wang, Di Zhang, Jing Xu, Minqiang Liu, Lin Wang, Dongsheng Gao, Erzhong Han, Chengxi Guo, Haonan Du, Bo Tao, Dacheng Zhang, Liangpei School of Computer Science Wuhan University Wuhan430072 China Institute of Artificial Intelligence Wuhan University Wuhan430072 China National Engineering Research Center for Multimedia Software Wuhan University Wuhan430072 China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan430072 China School of Computer Science Faculty of Engineering The University of Sydney Australia iFlytek Co Ltd National Engineering Research Center of Speech and Language Information Processing Hefei230088 China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China School of Computer Science and Engineering Nanyang Technological University Singapore Singapore
Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervised and self-supervised learning metho... 详细信息
来源: 评论
Biomedical data and AI
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Science China Life Sciences 2025年 第5期68卷 1536-1540页
作者: Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I
The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integratin...
来源: 评论
Selector-Enhancer: Learning Dynamic Selection of Local and Non-local Attention Operation for Speech Enhancement
arXiv
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arXiv 2022年
作者: Xu, Xinmeng Tu, Weiping Yang, Yuhong National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University China Hubei Luojia Laboratory China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University China
Attention mechanisms, such as local and non-local attention, play a fundamental role in recent deep learning based speech enhancement (SE) systems. However, natural speech contains many fast-changing and relatively br... 详细信息
来源: 评论
INJECTING SPATIAL INFORMATION FOR MONAURAL SPEECH ENHANCEMENT VIA KNOWLEDGE DISTILLATION
arXiv
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arXiv 2022年
作者: Xu, Xinmeng Tu, Weiping Yang, Yuhong National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University China Hubei Luojia Laboratory China
Monaural speech enhancement (SE) provides a versatile and cost-effective approach to SE tasks by utilizing recordings from a single microphone. However, the monaural SE lags performance behind multi-channel SE as the ... 详细信息
来源: 评论