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arXiv 2020年

作者： Chen, Yaran Gao, Ruiyuan Liu, Fenggang Zhao, Dongbin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 College of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Beihang Univercity Beijing China Beijing Institute of Technology Beijing China

—Although Neural Architecture Search (NAS) can bring improvement to deep models, they always neglect precious knowledge of existing models. The computation and time costing property in NAS also means that we should not start from scratch to search, but make every attempt to reuse the existing knowledge. In this paper, we discuss what kind of knowledge in a model can and should be used for new architecture design. Then, we propose a new NAS algorithm, namely ModuleNet, which can fully inherit knowledge from existing convolutional neural networks. To make full use of existing models, we decompose existing models into different modules which also keep their weights, consisting of a knowledge base. Then we sample and search for new architecture according to the knowledge base. Unlike previous search algorithms, and benefiting from inherited knowledge, our method is able to directly search for architectures in the macro space by NSGA-II algorithm without tuning parameters in these modules. Experiments show that our strategy can efficiently evaluate the performance of new architecture even without tuning weights in convolutional layers. With the help of knowledge we inherited, our search results can always achieve better performance on various datasets (CIFAR10, CIFAR100) over original architectures. Copyright © 2020, The Authors. All rights reserved.

关键词： Knowledge based systems

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Bio-inspired Modeling and Position control for Pneumatic Artificial Muscle

Bio-inspired Modeling and Position Control for Pneumatic Art...

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Youth Academic Annual Conference of Chinese Association of automation (YAC)

作者： Hang Fu Yang Liu Jiahao Chen School of Mechanical Engineering University of Science and Technology Beijing Beijing P. R. China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing P. R. China

ISBN: (数字)9781728176840

ISBN: (纸本)9781728176857

In this paper, the modeling and position control problem of a class of pneumatic artificial muscle (PAM) is investigated for the bio-inspired robotic manipulator. The system model of PAM is firstly developed based on experiment data identification. Then, the improved particle swarm optimization (PSO) control parameter tuning method is established for the effective position control of PAM. In particular, the concept of information entropy is used during the optimal procedure. In the end, the simulation results are given for demonstrating the effectiveness of the proposed design and control approach.

关键词： Simulation Position control Muscles Particle swarm optimization Information entropy Tuning Optimization

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A comprehensive survey on image aesthetic quality assessment 18

A comprehensive survey on image aesthetic quality assessment

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18th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2019

作者： Yang, Hongtao Shi, Ping He, Saike Pan, Da Ying, Zefeng Lei, Ling College of Information Engineering Communication University of China Beijing China School of Electrical and Information Engineering Beijing Polytechnic College Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728108018

Image aesthetic quality assessment has demonstrated tremendous success in variety of application domains in recent years. This field has been growing so rapidly that various approaches have been proposed trying to solve this challenging problem. This report presents a comprehensive survey on image aesthetic quality assessment, mainly focus on the contributions and novelties of the existing approaches recently. In this work, we firstly illustrate datasets related to image aesthetics and investigate feature extractions. Then five different aesthetic tasks are reviewed, including aesthetic classification, aesthetic regression, aesthetic distribution, aesthetic factors and aesthetic description. In addition, we reviewed recent applications concerning image aesthetics. Finally, different evaluation criterions in different literatures are summarized. We hope the survey could serve as a comprehensive reference and be useful for those who are interested in exploiting image aesthetic for their research. © 2019 IEEE.

关键词： Surveys

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Behavioral management for Employees based on Blockchain and Smart Contracts

Behavioral Management for Employees based on Blockchain and ...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Ni, Xiaochun Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China

ISBN: (纸本)9781728128535

With the continuing innovation of information and network technologies, on the one hand, social media has gradually become a necessary tool for internal communication within the organization, resulting in great changes in the behavioral patterns of employees;on the other hand, emerging technologies such as blockchain and smart contracts have enlightened many outstanding issues in organizational management, such as opaque data, tamable information and incomplete execution. Responding to the impact of new media on organizational management model, combined with the emerging technologies - blockchain and smart contracts, this paper aims to explore the behavioral management model of employees for trusted data within virtual cyberspace. It is devoted to the description modeling of employees' behavior and the guidance of employees' behavior based on smart contracts. We also validate our proposed method in a real-world scenario, and the experimental results prove our analysis, as well as the effectiveness of our approach. This paper is a basic research in the new application field, and is expected to offer helpful guidance and reference for future research efforts and industrial applications. © 2019 IEEE.

关键词： Smart contract

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Exploring Optimal Revenue Models for DSPs in Real Time Bidding Advertising

Exploring Optimal Revenue Models for DSPs in Real Time Biddi...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728128535

In RTB advertising, the AdExchange platform (AdX) can be regarded as a bridge connecting the supply side and demand side of advertising, and advertisers buy the ad impressions through the Demand-Side Platforms (DSPs). As such, there is a two-stage auction process for each ad impression, and the first stage is organized by the DSPs, while the second stage is organized by the AdX. In the two-stage auction process, two possible revenue models are available for DSPs, namely commission model and two-stage resale model. In this paper, we first compare the revenues of DSPs under the two models, and then explore the optimal revenue model for a DSP under the condition that the revenue model of other DSPs are given. We also unitize the computational experiments approach to evaluate our proposed method, and our results can help DSPs find their optimal revenue model in RTB advertising. © 2019 IEEE.

关键词： Marketing

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Real-world Robot Reaching Skill Learning Based on Deep Reinforcement Learning

Real-world Robot Reaching Skill Learning Based on Deep Reinf...

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第32届中国控制与决策会议

作者： Naijun Liu Tao Lu Yinghao Cai Rui Wang Shuo Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology of the Chinese Academy of Sciences

Traditional programming method can achieve certain manipulation tasks with the assumption that robot environment is known and ***,with robots gradually applied in more domains,robots often encounter working scenes which are complicated,unpredictable,and *** overcome the limitation of traditional programming method,in this paper,we apply deep reinforcement learning(DRL) method to train robot agent to obtain skill *** policy trained with DRL on real-world robot is time-consuming and costly,we propose a novel and simple learning paradigm with the aim of training physical robot ***,our method train a virtual agent in an simulated environment to reach random target position from random initial ***,virtual agent trajectory sequence obtained with the trained policy,is transformed to real-world robot command with coordinate transformation to control robot performing reaching *** show that the proposed method can obtain self-adaptive reaching policy with low training cost,which is of great benefits for developing intelligent and robust robot manipulation skill system.

关键词： Robot reaching skill learning deep reinforcement learning

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Attention grasping network: A real-time approach to generating grasp synthesis

Attention grasping network: A real-time approach to generati...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Gu, Qipeng Su, Jianhua Bi, Xueting Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences China Chinese Academy of Sciences Key Laboratory of Electromagnetic Radiation and Sensing Technology Institute of Electronics Beijing100190 China

ISBN: (纸本)9781728163215

This paper presents a real-time, pixelwise method to generate grasp synthesis based on fully convolutional netural networks (FCN). Our proposed Attention Grasping Network (AGN) applies a novel attention mechanism to robotic grasp detection, which automatically learns to focus on salient features of the input image. The model with attention mechnisms can compensate for the loss of detail information in standard FCN, which increases the sensitivity of the model and accuracy of prediction. In addition, in order to ensure a real-time grasp and save computing resources, the light-weight AGN model predicts the position and angle of grasping point. Our method only takes 22ms to execute the grasp detection pipeline on a GPU-equipped computer, and achieves 97.8% accuracy on Cornell Grasping Dataset. © 2019 IEEE.

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Color-sensitive person re-identification 28

Color-sensitive person re-identification

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28th International Joint Conference on Artificial Intelligence, IJCAI 2019

作者： Wang, Guan'an Yang, Yang Y. Cheng, Jian Wang, Jinqiao Hou, Zengguang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Beijing China

ISBN: (纸本)9780999241141

Recent deep Re-ID models mainly focus on learning high-level semantic features, while failing to explicitly explore color information which is one of the most important cues for person Re-ID model. In this paper, we propose a novel Color-Sensitive Re-ID to take full advantage of color information. On one hand, we train our model with real and fake images. By using the extra fake images, more color information can be exploited and it can avoid over-fitting during training. On the other hand, we also train our model with images of the same person with different colors. By doing so, features can be forced to focus on the color difference in regions. To generate fake images with specified colors, we propose a novel Color Translation GAN (CTGAN) to learn mappings between different clothing colors and preserve identity consistency among the same person with the clothing color. Extensive evaluations on two benchmark datasets show that our approach significantly outperforms state-of-the-art Re-ID models. © 2019 International Joint Conferences on Artificial Intelligence. All rights reserved.

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Parallel Building Process management System

Parallel Building Process Management System

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Chinese automation Congress (CAC)

作者： Sheng Liu Xisong Dong Gang Xiong Zhen Shen Bin Hu Xiaoyu Chen State Key Laboratory for Management and Control of Complex System Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426480

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved.

关键词： automation Digital twin Buildings User interfaces Software Engines Business

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Acupoint Detection Based on Deep Convolutional Neural Network

Acupoint Detection Based on Deep Convolutional Neural Networ...

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第三十九届中国控制会议

作者： Lingyao Sun Shiying Sun Yuanbo Fu Xiaoguang Zhao State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences school of Artificial Intelligence The Department of Acupuncture and Moxibustion Beijing Hospital of Traditional Chinese MedicineCapital Medical UniversityBeijing Key Laboratory of Acupuncture Neuromodulation

As an important component of Traditional Chinese Medicine(TCM),science of acupoint therapy has achieved significant results in clinical practice,but recognizing and positioning acupoints is heavily depends on the skills of *** recent years,researchers have proposed a few methods of automatic acupoints detection and positioning,but most of the methods are still based on manual designed *** this paper,we propose an acupoints detection method based on deep convolutional neural network,and an evaluation method is proposed for acupoint ***'s more,we build an acupoint detection *** are performed and a promising result is achieved.

关键词： convolutional neural network deep learning acupoint detection convolutional pose machine

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