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检索条件"机构=Department of Systems and Control Engineering Advanced Engineering Course"
1235 条 记 录,以下是351-360 订阅
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Pioneering the future of dentistry: AI-driven 3D bioprinting for next-generation clinical applications
Translational Dental Research
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Translational Dental Research 2025年 第1期1卷
作者: Zihui Liang Xiaohong Liao Huiyi Zong Xinyao Zeng Hong Liu Congcong Wu Kavya Keremane Bed Poudel Jun Yin Kai Wang Jin Qian Huanjiang Laboratory Zhejiang University Zhuji 311800 China National Local Joint Laboratory for Advanced Textile Processing and Clean Production Wuhan Textile University Wuhan 430073 China School of New Energy and Electrical Engineering Hubei University Wuhan 430073 China Department of Materials Science and Engineering The Pennsylvania State University University Park PA 16802 USA The State Key Laboratory of Fluid Power Transmission and Control Systems School of Mechanical Engineering Zhejiang University Hangzhou 310027 China
Artificial intelligence (AI) is revolutionizing dentistry by enhancing the analysis of complex medical imaging data, automating the identification of anatomical landmarks, and improving diagnostic accuracy and treatme... 详细信息
来源: 评论
On PID control for synchronization of complex dynamical network with delayed nodes
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Science China(Technological Sciences) 2019年 第8期62卷 1412-1422页
作者: GU HaiBo Lv JinHu LIN ZongLi Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence Beihang University Beijing 100083 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 USA
Over the past two decades, synchronization, as an interesting collective behavior of complex dynamical networks, has been attracting much attention. To reveal and analyze the inherent mechanism of synchronization in c... 详细信息
来源: 评论
Adaptive future frame prediction with ensemble network
arXiv
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arXiv 2020年
作者: Kim, Wonjik Tanaka, Masayuki Okutomi, Masatoshi Sasaki, Yoko Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Meguto-kuTokyo152-8550 Japan Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology Koto-ku Tokyo135-0064 Japan
Future frame prediction in videos is a challenging problem because videos include complicated movements and large appearance changes. Learning-based future frame prediction approaches have been proposed in kinds of li... 详细信息
来源: 评论
Learning-based human segmentation and velocity estimation using automatic labeled lidar sequence for training
arXiv
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arXiv 2020年
作者: KIM, WONJIK TANAKA, MASAYUKI OKUTOMI, MASATOSHI SASAKI, YOKO Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Meguro-ku Tokyo152-8550 Japan Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology Koto-ku Tokyo135-0064 Japan
In this paper, we propose an automatic labeled sequential data generation pipeline for human segmentation and velocity estimation with point clouds. Considering the impact of deep neural networks, state-of-the-art net... 详细信息
来源: 评论
Increasing Part Geometric Accuracy in High Speed Machining using Cascade Iterative Learning control  9
Increasing Part Geometric Accuracy in High Speed Machining u...
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9th CIRP Conference on High Performance Cutting, HPC 2020
作者: Ward, Rob Ozkirimli, Omer Jones, Bryn Industrial Doctorate Centre in Machining Science Advanced Manufacturing Research Centre with Boeing University of Sheffield Rotherham S60 5TZ United Kingdom Machining Dynamics Research Group Advanced Manufacturing Research Centre with Boeing University of Sheffield Rotherham S60 5TZ United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom
High speed machining provides high productivity and low machining cycle times. Post machining, there can exist differences between desired and measured part geometry due to tool deflection induced from higher feedrate... 详细信息
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Distributed Model-Free Adaptive Learning control of Discrete-Time Nonlinear Multiagent systems
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IEEE Transactions on Neural Networks and Learning systems 2025年 PP卷 PP页
作者: Ma, Yong-Sheng Che, Wei-Wei Xu, Shi-Xu Deng, Chao Wu, Zheng-Guang Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems School of Automation Beijing100081 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries College of Information Science and Engineering Shenyang110819 China Qingdao University Shandong Key Laboratory of Industrial Control Technology Department of Automation Qingdao266071 China Nanjing University of Posts and Telecommunications Institute of Advanced Technology Nanjing210000 China Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou310027 China
This article investigates the distributed control problem for nonlinear multiagent systems (MASs) with unknown system models. A novel distributed model-free adaptive learning algorithm is developed to learn a controll... 详细信息
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Research on path planning of robot based on deep reinforcement learning
Research on path planning of robot based on deep reinforceme...
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第三十九届中国控制会议
作者: Feng Liu Chang Chen Zhihua Li Zhi-Hong Guan Hua O Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems College of Automation Huazhong University of Science and Technology Department of Mechanical Engineering Boston University
In this paper, to avoid the problem of local optimization and slow convergence in complex environment, a reinforcement learning algorithm is proposed to solve the problem. A robot path planning model is built and its ... 详细信息
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controlling a Networked SIS Model via a Single Input over Undirected Graphs ⁎
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IFAC-PapersOnLine 2020年 第2期53卷 10981-10986页
作者: Dan Wang Ji Liu Philip E. Paré Wei Chen Li Qiu Carolyn L. Beck Tamer Başar Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong China Department of Electrical and Computer Engineering Stony Brook University NY 11794 USA Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Mechanics and Engineering Science & Beijing Innovation Center for Engineering Science and Advanced Technology Peking University Beijing China Coordinated Science Laboratory University of Illinois at Urbana-Champaign IL 61801 USA
This paper formulates and studies the problem of controlling a networked SIS model using a single input in which the network structure is described by a connected undirected graph. A necessary and sufficient condition...
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Improved potential field method path planning based on genetic algorithm
Improved potential field method path planning based on genet...
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第三十九届中国控制会议
作者: Feng Liu Hualing He Zhihua Li Zhi-Hong Guan Hua O Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems College of Automation Huazhong University of Science and Technology Department of Mechanical Engineering Boston University
In order to overcome the problem of path planning failure in traditional potential field method, an improved potential field path planning method based on genetic algorithm is proposed in this paper. Firstly, for the ... 详细信息
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A 3D-printed microfluidic device for fabricating the soft, hollow, double-network magnetic microrobots
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Microchemical Journal 2025年 215卷
作者: Wu, Jialin Wang, Jie Xu, Shanshan Zou, Ruiping Yu, Aibing Liu, Minsu Yan, Sheng Institute for Advanced Study Shenzhen University Shenzhen 518060 China ARC Research Hub for Smart Process Design and Control Department of Chemical and Biological Engineering Monash University Clayton 3800 VIC Australia Centre for Simulation and Modelling of Particulate Systems Southeast University Suzhou 215000 China Research Center for Smart Process Engineering Great Bay University Dongguan 523000 China Monash Suzhou Research Institute (MSRI) Monash University Suzhou 215000 China
Endovascular intervention has transformed minimally invasive surgery but faces challenges in device stiffness, navigability, and safety. Existing magnetic soft robots, while promising, often risk incomplete retrieval ... 详细信息
来源: 评论