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检索条件"机构=Laboratory of Modular Data Processing and Control Systems"
43 条 记 录,以下是21-30 订阅
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A Model of the Russia's Agriculture Readiness for Digital Transformation  13
A Model of the Russia's Agriculture Readiness for Digital Tr...
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13th International Conference Management of Large-Scale System Development, MLSD 2020
作者: Kulba, Vladimir Medennikov, Viktor V.A. Trapeznikov Institute of Control Sciences of Ras Laboratory of Modular Data Processing and Control Systems Moscow Russia Federal Research Center "computer Science and Control" of the Russian Academy of Sciences Information and Computing Systems Department Moscow Russia
The paper discusses the problems of the effective implementation of digital technology in Russia's agriculture and how to solve the same by comprehensive and integrative methods. We present a mathematical model of... 详细信息
来源: 评论
Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison
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IEEE/CAA Journal of Automatica Sinica 2023年 第4期10卷 957-968页
作者: Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China
Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the... 详细信息
来源: 评论
Convergent Methodology for National Digital Agriculture Platform
Convergent Methodology for National Digital Agriculture Plat...
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World Conference on Smart Trends in systems, Security and Sustainability (WorldS4)
作者: Alexander Raikov Laboratory of modular data processing and control systems Institute of Control Sciences RAS Moscow Russia
This paper addresses the issue of building the methodology of creating the national digital agriculture platform (ecosystem). The problem was to ensure integrating some different strategic approaches when the goals ar... 详细信息
来源: 评论
Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning  22
Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...
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22nd IEEE International Conference on Industrial Informatics, INDIN 2024
作者: Cao, Weipeng Yao, Xuyang Xu, Zhiwu Pan, Yinghui Sun, Yixuan Li, Dachuan Qiu, Bohua Wei, Muheng Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China
Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output ... 详细信息
来源: 评论
Ascl: Accelerating Semi-Supervised Learning Via Contrastive Learning
SSRN
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SSRN 2024年
作者: Liu, Haixiong Li, Zuoyong Wu, Jiawei Zeng, Kun Hu, Rong Zeng, Wei Fujian Provincial Key Laboratory of Big Data Mining and Applications School of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Data Science Minjiang University Fuzhou350121 China School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Guangdong Shenzhen518107 China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Wuyishan354300 China School of Physics and Mechanical and Electrical Engineering Longyan University Longyan364012 China
SSL(Semi-supervised learning) is widely used in machine learning, which leverages labeled and unlabeled data to improve model performance. SSL aims to optimize class mutual information, but noisy pseudo-labels introdu... 详细信息
来源: 评论
A Model of the Russia’s Agriculture Readiness for Digital Transformation
A Model of the Russia’s Agriculture Readiness for Digital T...
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International Conference on Management of Large-Scale System Development (MLSD)
作者: Vladimir Kulba Viktor Medennikov Laboratory of modular data processing and control systems V.A. Trapeznikov Institute of Control Sciences of RAS Moscow Russia Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia
The paper discusses the problems of the effective implementation of digital technology in Russia's agriculture and how to solve the same by comprehensive and integrative methods. We present a mathematical model of... 详细信息
来源: 评论
Analytical and Instrumental Framework for The Analysis and Resolution of Stakeholder Interest Conflict Using Cognitive Maps
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Journal of Physics: Conference Series 2021年 第1期1828卷
作者: Z K Avdeeva S V Kovriga Russian Academy Sciences V.A. Trapeznikov Institute of Control Sciences Laboratory of modular data processing and control systems Moscow Russia
The statement of the basic control problem of a situation with many active stakeholders using cognitive maps is presented. Approaches to the analysis and resolution of interest conflicts in such situations based on th...
来源: 评论
Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning
Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...
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IEEE International Conference on Industrial Informatics (INDIN)
作者: Weipeng Cao Xuyang Yao Zhiwu Xu Yinghui Pan Yixuan Sun Dachuan Li Bohua Qiu Muheng Wei Guangdong Laboratory of Artificial Intelligence and Digital Economy (Shenzhen) Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China
Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output ... 详细信息
来源: 评论
Mobility in China, 2020: a tale of four phases
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National Science Review 2021年 第11期8卷 110-120页
作者: Suoyi Tan Shengjie Lai Fan Fang Ziqiang Cao Bin Sai Bing Song Bitao Dai Shuhui Guo Chuchu Liu Mengsi Cai Tong Wang Mengning Wang Jiaxu Li Saran Chen Shuo Qin Jessica R.Floyd Zhidong Cao Jing Tan Xin Sun Tao Zhou Wei Zhang Andrew J.Tatem Petter Holme Xiaohong Chen Xin Lu College of Systems Engineering National University of Defense Technology WorldPop School of Geography and Environmental ScienceUniversity of Southampton School of Mathematics and Big Data Foshan University State Key Laboratory on Blind Signal Processing State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Chinese Evidence-Based Medicine Center National Clinical Research Center for Geriatrics West China Hospital Sichuan University Big Data Research Center University of Electronic Science and Technology of China West China Biomedical Big Data Center West China Hospital Sichuan University Tokyo Tech World Hub Research Initiative Institute of Innovative Research Tokyo Institute of Technology School of Business Central South University Institute of Big Data and Internet Innovations Hunan University of Technology and Business
2020 was an unprecedented year,with rapid and drastic changes in human mobility due to the COVID-19 *** understand the variation in commuting patterns among the Chinese population across stable and unstable periods,we... 详细信息
来源: 评论
Optimization of Grouping Evacuation Strategy in High-rise Building Fires Based on Graph Theory and Computational Experiments
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IEEE/CAA Journal of Automatica Sinica 2018年 第6期5卷 1104-1112页
作者: Yuling Hu Xiwei Liu School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing 100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing 100044China State Key Laboratory fo Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing 100190China Qingdao Academy of Intelligent Industries Qingdao 266109China
It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grou... 详细信息
来源: 评论