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31st IEEE/CVF Conference on computer Vision and Pattern Recognition (CVPR)

作者： Wang, Qiang Teng, Zhu Xing, Junliang Gao, Jin Hu, Weiming Maybank, Stephen University of Chinese Academy of Sciences Beijing China School of Computer and Information Technology Beijing Jiaotong University Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Department of Computer Science and Information Systems Birkbeck College University of London UK

ISBN: (纸本)9781538664209

Offline training for object tracking has recently shown great potentials in balancing tracking accuracy and speed. However, it is still difficult to adapt an offline trained model to a target tracked online. This work presents a Residual Attentional Siamese Network (RASNet) for high performance object tracking. The RASNet model reformulates the correlation filter within a Siamese tracking framework, and introduces different kinds of the attention mechanisms to adapt the model without updating the model online. In particular, by exploiting the offline trained general attention, the target adapted residual attention, and the channel favored feature attention, the RASNet not only mitigates the over-fitting problem in deep network training, but also enhances its discriminative capacity and adaptability due to the separation of representation learning and discriminator learning. The proposed deep architecture is trained from end to end and takes full advantage of the rich spatial temporal information to achieve robust visual tracking. Experimental results on two latest benchmarks, OTB-2015 and VOT2017, show that the RASNet tracker has the state-of-the-art tracking accuracy while runs at more than 80 frames per second.

关键词： Target tracking Correlation Feature extraction Training Adaptation models Visualization Object tracking

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The Chinese ‘‘HumanFlesh’’ Web:the first decade and beyond

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Chinese Science Bulletin 2014年第26期59卷 3352-3361页

作者： Fei-Yue Wang Daniel Zeng Qingpeng Zhang James A. Hendler Jianping Cao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Department of Management Information Systems The University of Arizona Tucson Department of Systems Engineering and Engineering Management City University of Hong Kong Tetherless World Constellation Department of Computer Science Rensselaer Polytechnic Institute Troy The Research Center for Computational Experiments and Parallel Systems National University of Defense Technology

Human flesh search(HFS), a Web-enabled crowdsourcing phenomenon, originated in China a decade ago. In this article, we present the first comprehensive empirical analysis of HFS, focusing on the scope of HFS activities, the patterns of HFS crowd collaboration process, and the characteristics of HFS participant networks. A survey of HFS participants was conducted to provide an in-depth understanding of the HFS community and various factors that motivate these participants to contribute. This article also advocates a new stream of Web science and social computing research that will be important in predicting the future growth and use of the World Wide Web.

关键词：中国人网址肉 Web功能实证分析参与者共同体万维网

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Computational Experiments for Complex Social systems:Experiment Design and Generative Explanation

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1022-1038页

作者： Xiao Xue Deyu Zhou Xiangning Yu Gang Wang Juanjuan Li Xia Xie Lizhen Cui Fei-Yue Wang the School of Computer Software College of Intelligence and ComputingTianjin UniversityTianjin 300350China the School of Software and the Joint SDUNTU Centre for Artificial Intelligence Research(C-FAIR) Shandong UniversityJinan 250101China the Information School Xi’an University of Financial and EconomicsXi’an 710100China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Hainan University Haikou 570228China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 1001901China

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system *** address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating ***,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

关键词： Agent-based modeling computational experiments cyber-physical-social systems(CPSS) generative deduction generative experiments meta model

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A Region Enhanced Discrete Multi-Objective Fireworks Algorithm for Low-Carbon Vehicle Routing Problem

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Complex System Modeling and Simulation 2022年第2期2卷 142-155页

作者： Xiaoning Shen Jiaqi Lu Xuan You Liyan Song Zhongpei Ge Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Big Data Analysis TechnologySchool of AutomationNanjing University of Information Science and TechnologyNanjing 210044China School of Automation Nanjing University of Information Science and TechnologyNanjing 210044China Institute of Trustworthy Autonomous Systems and also with the Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent ComputationDepartment of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

A constrained multi-objective optimization model for the low-carbon vehicle routing problem(VRP)is established.A carbon emission measurement method considering various practical factors is *** minimizes both the total carbon emissions and the longest time consumed by the sub-tours,subject to the limited number of available *** to the characteristics of the model,a region enhanced discrete multi-objective fireworks algorithm is proposed.A partial mapping explosion operator,a hybrid mutation for adjusting the sub-tours,and an objective-driven extending search are designed,which aim to improve the convergence,diversity,and spread of the non-dominated solutions produced by the algorithm,*** low-carbon VRP instances with different scales are used to verify the effectiveness of the new ***,comparison results with four state-of-the-art algorithms indicate that the proposed algorithm has better performance of convergence and distribution on the low-carbon *** provides a promising scalability to the problem size.

关键词： vehicle routing problem carbon emission multi-objective optimization fireworks algorithm region enhanced

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Managing implicit requirements using semantic case-based reasoning research preview

Managing implicit requirements using semantic case-based rea...

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18th Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2012

作者： Daramola, Olawande Moser, Thomas Sindre, Guttorm Biffl, Stefan Department of Computer and Information Science Norwegian University of Science and Technology Trondheim Norway Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems Vienna University of Technology Austria

ISBN: (纸本)9783642287138

[Context and motivation] Implicit requirements (ImRs) are defined as requirements of a system which are not explicitly expressed during requirements elicitation, often because they are considered so basic that developers should already know them. Many products have been rejected or users made unhappy because implicit requirements were not sufficiently addressed. [Question/Problem] Requirement management tools have not addressed the issue of managing ImRs, also despite the challenges of managing ImRs that exist in practice the issue has not received sufficient attention in the literature. [Principal Idea/results] This planned research will investigate how automated support can be provided for managing ImRs within an organizational context, which is currently lacking in practice. This work proposed an approach that is based on semantic case-based reasoning for managing ImRs. [Contribution] We present the concept of a tool which enables managing of ImRs through the analogy-based requirements reuse of previously known ImRs. This ensures the discovery, structured documentation, proper prioritization, and evolution of ImRs, which improves the overall success of software development processes. © 2012 Springer-Verlag.

关键词： Case based reasoning

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User Experience Evaluation in Virtual Reality based on Subjective Feelings and Physiological Signals

User Experience Evaluation in Virtual Reality based on Subje...

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2020 Engineering Reality of Virtual Reality Conference, ERVR 2020

作者： Niu, Yunfang Wang, Danli Wang, Ziwei Sun, Fan Yue, Kang Zheng, Nan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Computer and Information Technology Liaoning Normal University Dalian China

At present, the research on emotion in the virtual environment is limited to the subjective materials, and there are very few studies based on objective physiological signals. In this article, the authors conducted a user experiment to study the user emotion experience of virtual reality (VR) by comparing subjective feelings and physiological data in VR and two-dimensional display (2D) environments. First, they analyzed the data of self-report questionnaires, including Self-assessment Manikin (SAM), Positive And Negative Affect Schedule (PANAS) and Simulator Sickness Questionnaire (SSQ). The result indicated that VR causes a higher level of arousal than 2D, and easily evokes positive emotions. Both 2D and VR environments are prone to eye fatigue, but VR is more likely to cause symptoms of dizziness and vertigo. Second, they compared the differences of electrocardiogram (ECG), skin temperature (SKT) and electrodermal activity (EDA) signals in two circumstances. Through mathematical analysis, all three signals had significant differences. Participants in the VR environment had a higher degree of excitement, and the mood fluctuations are more frequent and more intense. In addition, the authors used different machine learning models for emotion detection, and compared the accuracies on VR and 2D datasets. The accuracies of all algorithms in the VR environment are higher than that of 2D, which corroborated that the volunteers in the VR environment have more obvious skin electrical signals, and had a stronger sense of immersion. This article effectively compensated for the inadequacies of existing work. The authors first used objective physiological signals for experience evaluation and used different types of subjective materials to make contrast. They hope their study can provide helpful guidance for the engineering reality of virtual reality. c Society for Imaging Science and Technology 2019

关键词： Virtual reality

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On the peculiarities of the exchange of data between applications in high-level languages and matlab functions 1

On the peculiarities of the exchange of data between applica...

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1st Workshop computer Science and Engineering in the framework of the 5th International Scientific-Methodical Conference "Problems of Mathematical and Natural-Scientific Training in Engineering Education, CSITinMNSTinEE 2018

作者： Krasnovidov, Alexander V. Khomonenko, Anatoly D. Zabrodin, Andrew V. Smirnov, Alexander V. Department of Information and Computer Systems Emperor Alexander I St. Petersburg State Transport University St. Petersburg Russia Laboratory of Computer Aided Integrated Systems St.Petersburg Institute for Informatics and Automation of the RAS Saint Petersburg Russia

The possibilities of data exchange between functions in the language of the Matlab system with applications in high-level languages are considered. Programs in high-level languages appropriately to use in conjunction with mathematical packages to collect data, control various technological processes, and perform other similar actions. The instrumental means of organizing such an exchange are characterized. It had been shown the feasibility of integrating applications in high-level languages and the M-function of the Matlab system, if necessary, to organize input / output of large amounts of data. Copyright © by the papers’ authors.

关键词： Electronic data interchange

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A Comparison for Probabilistic Spiking Neuron Model and Spiking Integrated and Fired Neuron Model 33

A Comparison for Probabilistic Spiking Neuron Model and Spik...

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第三十三届中国控制会议

作者： WANG Xiuqing HOU Zeng-Guang ZENG Hui TAN Min WANG Yongji Hebei Normal University State Key Laboratory of Complex Systems and Intelligence Science Institute of AutomationChinese Academy of Sciences School of Information University of Science and Technology Beijing Laboratory for Internet Technologies State Key Laboratory of Computer ScienceInstitute of SoftwareChinese Academy of Sciences

ISBN: (纸本)9781479947249

As the third generation of artificial neural networks(ANNs), spiking neural networks(SNNs) have many advantages over the traditional ones. Selecting proper spiking neuron models for the design of SNNs is important. In this paper, schematic and training algorithm of spiking integrated and fired(IAF) neuron model and probability spiking neuron model(pSNM) are introduced. By comparing the classification results for mobile robots' corridor-scene-classifier based on IAF model and pSNM,and the control results of mobile robots' wall-following controller based on spiking IAF model and pSNM, the similarities and differences between the two models are discussed. The similar and different features of the two spiking neuron models are obtained. IAF model is more suitable for the design of mobile robots controller than that of pSNM. While pSNM has better noise robust than IAF model. Spiking IAF model and pSNM are suitable for different situations.

关键词： Spiking neural network,Spiking integrated and fired neuron model,Probability spiking neuron model,Spiking time-delayed encoding,Spiking frequency encoding

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Deep Learning-based Moving Object Segmentation:Recent Progress and Research Prospects

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Machine Intelligence Research 2023年第3期20卷 335-369页

作者： Rui Jiang Ruixiang Zhu Hu Su Yinlin Li Yuan Xie Wei Zou College of Information Engineering Shanghai Maritime UniversityShanghai201306China School of Computer Science and Technology East China Normal UniversityShanghai200062China Research Center of Precision Sensing and Control Institute of AutomationChinese Academy of SciencesBeijing100190China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China

Moving object segmentation(MOS),aiming at segmenting moving objects from video frames,is an important and challenging task in computer vision and with various *** the development of deep learning(DL),MOS has also entered the era of deep models toward spatiotemporal feature *** paper aims to provide the latest review of recent DL-based MOS methods proposed during the past three ***,we present a more up-to-date categorization based on model characteristics,then compare and discuss each category from feature learning(FL),and model training and evaluation *** FL,the methods reviewed are divided into three types:spatial FL,temporal FL,and spatiotemporal FL,then analyzed from input and model architectures aspects,three input types,and four typical preprocessing subnetworks are *** terms of training,we discuss ideas for enhancing model *** terms of evaluation,based on a previous categorization of scene dependent evaluation and scene independent evaluation,and combined with whether used videos are recorded with static or moving cameras,we further provide four subdivided evaluation setups and analyze that of reviewed *** also show performance comparisons of some reviewed MOS methods and analyze the advantages and disadvantages of reviewed MOS methods in terms of ***,based on the above comparisons and discussions,we present research prospects and future directions.

关键词： Moving object segmentation(MOS) change detection background subtraction deep learning(DL) video understanding

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Neural Network Adaptive Critic Control With Disturbance Rejection 29

Neural Network Adaptive Critic Control With Disturbance Reje...

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第29届中国控制与决策会议

作者： Ding Wang Chaoxu Mu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences School of Electrical and Information Engineering Tianjin University School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509046584

A neural-network-based adaptive critic control method is established for continuous-time input-affine uncertain nonlinear systems to achieve disturbance *** present problem can be formulated as a two-player zero-sum differential game and the adaptive critic mechanism is employed to solve the minimax optimization problem.A neural network identifier is developed to reconstruct the unknown dynamical *** optimal control law and the worst-case disturbance law are designed by introducing and training a critic neural *** effectiveness of the present self-learning control method is also illustrated by a simulation experiment.

关键词： Adaptive critic control Adaptive dynamic programming Approximate dynamic programming Disturbance rejection Learning systems Neural networks Nonlinear control

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