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3D Face Reconstruction system From A Single Photo Based On Regression Neural Network

IFAC-PapersOnLine 2020年第5期53卷 71-76页

作者： Yatai Ji Keqiang Li Huaiyu Wu Gang Xiong Zhen Shen Xiuqin Shang Bangwen Xi The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Automation Tsinghua University Beijing 100084 China University of Chinese Academy of Sciences Beijing 100049 China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan 523808 China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China

3D human face modeling is one of the most popular research directions in the field of computer stereo vision. On the one hand, the complex physiological structure of human face as well as various expressions and attitude changes bring great challenges to three-dimensional modeling, which makes the modeling method of human face have high research value and reference significance. On the other hand, 3D face reconstruction has a broad application prospect, and the application demand attracts more researchers to invest in it. Based on the 3DMM and 3DDFA method, this paper utilizes regression neural network to realize end-to-end face reconstruction. After that, we build a visualization program with the training model to realize face modeling based on a single face image of any pose or expression. It’s a 3D face reconstruction system which has functions such as face alignment, face rotation and so on.

关键词： face reconstruct 3DMM 3DDFA regression network

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Parallel intelligence： toward lifelong and eternal developmental AI and learning in cyber-physical-social spaces

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Frontiers of Computer Science 2018年第3期12卷 401-405页

作者： Fei-Yue WANG Jun Jason ZHANG Xiao WANG The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Electrical Engineering Wuhan University Wuhan 430072 China Qingdao Academy of Intelligent Industries Qingdao 266109 China

Dear editor, Fundamentally, there are only two main approaches so far in artificial intelligence （AI）： reasoning-oriented formal logic approach and function-oriented computational intelligence approach, so called Neats vs. Scuruffies, which is a reflection of the historical fight between two schools of thought for formalism and empiricism respectively in the field of AI that is continuing even today.

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A Vision-Based Path Planning and Following system for a Miniature Robotic Fish

A Vision-Based Path Planning and Following System for a Mini...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Yue Lu Xingyu Chen Zhengxing Wu Yan Yan Junzhi Yu University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Turbulence and Complex System BIC-ESAT College of Engineering Peking University Beijing China

ISBN: (数字)9781728137261

ISBN: (纸本)9781728137278

Most existing path following algorithms for middle-or large-sized underwater vehicles minimize yaw difference of the control object. Breaking the canonical manner, this paper presents a vision-based path planning and following system for miniature robotic fish. As for path planning, the proposed system finds a gird path based on the AStar algorithm and selects a series of target points in the grid path. By connecting these points in order, a curve path can be planned. In terms of path following, the proposed system forgoes to give a specific yaw and only uses a global camera. It obtains coordinates of the robotic fish in real time by KCF tracking algorithm to calculate an approximate motion vector. A PID controller is employed to drive the difference angle between the motion vector and the target vector (the vector from the robotic fish to the target point) to zero. By swimming to target points one by one, the robotic fish can move to the terminus following the planned path. Finally, aquatic experiments are conducted to verify the effectiveness of the vision-based path planning and following system. The results reveal that the developed system can generate a safe and smooth path, and the robotic fish can follow the path with acceptable deviation.

关键词： Fish Robot kinematics Path planning Robot sensing systems Solenoids Magnetic resonance imaging

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INDReview on Facial Expression Analysis and its Application in Education

INDReview on Facial Expression Analysis and its Application ...

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Chinese Automation Congress (CAC)

作者： Qiang Li Xiwei Liu Xiaoyan Gong Sifeng Jing The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Institute of Smart Education Systems Qingdao Academy of Intelligent Industries BeiJing China

In recent years, with the rapid development of computer technology, facial expression recognition technology has gradually been applied to primary and secondary schools. This article first introduces the application of facial expression recognition in education. Then the development of facial expression recognition and the four basic processes of facial expressions are described. After that, the methods and algorithms used in face detection and localization of face expression recognition and classification are summarized, feature extraction and classification are summarized. Finally, the current application of facial expression recognition technology in education and the existing problems and future development are pointed out.

关键词： Face recognition Classification algorithms Feature extraction Education Hidden Markov models Face detection Face

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Load Curve Modeling Based on Behavior Analysis of Distributed Power Customers

Load Curve Modeling Based on Behavior Analysis of Distribute...

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2019 4th Asia Conference on Power and Electrical Engineering (ACPEE 2019)

作者： Xinyang HAN Yu ZHANG Yuqiao JIAO Yue ZHANG Yanjing QU Min DING State Grid Energy Research Institute School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Shanghai Municipal Electric Power Company

As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load,this paper proposes a load curve modeling method for renewable power customers based on the behavior ***,customers' active behavior is represented by the quantity of active customer *** on the analysis of customer behaviors,a modeling method for the quantity of active customer households is proposed based on Markov Chain Monte Carlo ***,with the inputs as the quantity of active customer households and time of photovoltaic power generation,an inference model based on fuzzy logic is proposed to get the quantity of customer household starting electrical *** combing the average usage time of electrical appliances,load characteristics are analyzed based on usage state of electrical appliance of distributed power ***,the simulation results verify the effectiveness of the proposed method.

关键词： Carlo Monte Markov Load Curve Modeling Based on Behavior Analysis of Distributed Power Customers

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Artificial Neural Network Based Maximum Power Point Tracking for PV system

Artificial Neural Network Based Maximum Power Point Tracking...

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第三十八届中国控制会议

作者： Al-wesabi Ibrahim Min Ding Xiaoling Jin Xianzhong Dai Mohammad Abu Sarhan Muhammed Badeaa Shafik Hao Zhou School of Automation China University of Geoscience Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Energy Research Institute School of electrical engineering and automation Wuhan university

Nowadays PV systems is suffering from two main problems: high production cost and low efficiency especially under variable weather conditions. Therefore, to reduce such associated problems, PV systems are being connected with various optimization controllers such as maximum power point tracking. In this paper, an artificial neural network maximum power point method has been designed to be linked between a PV system and DC-DC buck converter, and each part of the system is fully explained. The whole system was modeled under MATLAB/Simulink environment, simulation results demonstrated the efficiency of the proposed method. The proposed method has been examined to track the maximum power point under different weather conditions which shows a rapid and accurate tracking of the maximum power point(MPP) of PV system. The whole system which consists of PV arrays, Buck converter, ANN tracker, and load has been modeled using MATLAB/Simulink environment. This Simulink model has been examined using different levels of temperature and irradiation and the output results of both P-V and I-V characteristics, output power, and the system efficiency clearly demonstrate the validation of the modeled system. This demonstration has been done by comparing between the result of experimental platform and the results of simulated model which approves that ANN is highly recommended to be used in the field of maximum power point tracking of PV system.

关键词： Artificial neural network(ANN) Photovoltaic(PV) Maximum power point tracking(MPPT) Buck converter

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Digital Quadruplets for Cyber-Physical-Social systems based Parallel Driving: From Concept to Applications

arXiv

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arXiv 2020年

作者： Liu, Teng Yang, Xing Wang, Hong Tang, Xiaolin Chen, Long Yu, Huilong Wang, Fei-Yue State Key Laboratory of Mechanical Transmissions College of Automotive Engineering Chongqing University Chongqing400044 China Department of Mechanical and Aerospace Engineering Nanyang Technological University Singapore School of Vehicle and Mobility Tsinghua University Beijing China Waytous Inc. Qingdao Shandong266109 China Department of Mechanical and Mechatronics Engineering University of Waterloo N2L 3G1 Canada State Key Laboratory for Management and Control of Complex System Institute of Automation Beijing China

Digital quadruplets aiming to improve road safety, traffic efficiency and driving cooperation for future connected automated vehicles are proposed with the enlightenment of ACP based parallel driving. The ACP method denotes Artificial societies, Computational experiments and Parallel execution modules for cyber-physical-social systems. Four agents are designed in the framework of digital quadruplets: descriptive vehicles, predictive vehicles, prescriptive vehicles and real vehicles. The three virtual vehicles (descriptive, predictive, and prescriptive) dynamically interact with the real one in order to enhance the safety and performance of the real vehicle. The details of the three virtual vehicles in the digital quadruplets are described. Then, the interactions between the virtual and real vehicles are presented. The experimental results of the digital quadruplets demonstrate the effectiveness of the proposed framework. Copyright © 2020, The Authors. All rights reserved.

关键词： Vehicles

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A Blockchain-based Educational Digital Assets management system

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IFAC-PapersOnLine 2020年第5期53卷 47-52页

作者： Junqing Li Mo Lan Ying Tang Shichao Chen Fei-Yue Wang Wei Wei Shandong University of Science and Technology Qingdao China 266590 The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China 100190 Southwest University Chongqing China 400715 Beijing Achievelearn Education Technology Group Beijing China 100095 Electrical and Computer Engineering Rowan University Glassboro NJ 08003 USA Qingdao Academy of Intelligent Industries Qingdao China 266042 3E Smart Education Beijing China 100083

A variety of heterogeneous information is produced after the application of various emerging technologies in education, which is of great research value as educational assets. The traditional educational asset management system has emerged. In view of the disadvantages of traditional system centralization process, people begin to use decentralized blockchain technology for innovation. This paper proposes an educational digital asset management system architecture based on blockchain 3.0 technology system, which forms various data formed by students in and out of class learning process, courseware and experience data generated by teachers in the process of teaching into educational digital assets, and carries out the right confirmation and storage on the blockchain. The system can use a variety of heterogeneous data in digital assets to analyze the development status of school users, achieve the teaching purpose of teaching students according to their aptitude and different people.

关键词： blockchain blockchain system digital assets educational technology decentralized systems

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Comparative Study of Four Speed controllers of Brushless DC Motors for Industrial Applications

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IFAC-PapersOnLine 2020年第5期53卷 59-64页

作者： Tariku Sinshaw Tamir Gang Xiong Zhen Shen Xiaoyan Gong Sheng Liu Ehtisham Lodhi Li Wan Xisong Dong State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan 523808 China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China Ten Dimensions (Guangdong) Technology Co. Ltd. Foshan 528225 China

Direct current (DC) motors are one of the most important kind of motors and are widely used in robotic and industrial applications. Recently, there have been significant efforts to develop direct current (DC) motors in an attempt to control speed of motors. However, conventional controlling approaches perform undesirably in terms of stability and quick response. Therefore, this paper presents a hybrid intelligent controller configuration for optimized speed control of brushless direct current (BLDC) motors in a factory supervisory control data acquisition (SCADA) system. We compare this hybrid intelligent controller with a conventional PID controller, fuzzy logic controller (FLC), and artificial neural network model reference controller (ANNMRC) in MATLAB , and the results show that the hybrid (neuro-fuzzy) controller performs superior in terms of stability, speed trajectory tracking capability, fast response, and simplicity for implementation.

关键词： BLDC motor fuzzy logic controller (FLC) artificial neural network model reference controller (ANNMRC) hybrid (neuro-fuzzy) control

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Singular Perturbation Approach based Boundary control of a Flexible Manipulator with High Gain Observer

Singular Perturbation Approach based Boundary Control of a F...

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第三十八届中国控制会议

作者： Zhijie Liu Hongjun Yang Yan Yang School of Automation and Electrical Engineering University of Science and Technology Beijing The State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Electro-Mechanical Engineering Xidian University

In this study, boundary control of a flexible manipulator is developed on the basis of the dynamic, partial differential equation(PDE) model. One of the main contributions is that the high gain observer is first applied to the PDE model of a flexible manipulator instead of measuring link velocity and end actuator velocity. In addition, using singular perturbation approach the PDE model is divided into two simpler subsystems to simplify the control design. Based on the proposed observer and decoupled PDE model, a sliding mode boundary control is designed to regulate angular position and suppress elastic vibration simultaneously. Numerical simulations demonstrate the effectiveness of the proposed scheme.

关键词： Boundary control flexible manipulator PDE model high gain observer singular perturbation

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