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Vehicle License Plate Recognition Based on Extremal Regions and Restricted Boltzmann Machines

IEEE TRANSACTIONS ON intelligent TRANSPORTATION systems 2016年第4期17卷 1096-1107页

作者： Gou, Chao Wang, Kunfeng Yao, Yanjie Li, Zhengxi Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Natl Univ Def Technol Res Ctr Computat Expt & Parallel Syst Changsha 410073 Hunan Peoples R China North China Univ Technol Beijing 100041 Peoples R China

This paper presents a vehicle license plate recognition method based on character-specific extremal regions (ERs) and hybrid discriminative restricted Boltzmann machines (HDRBMs). First, coarse license plate detection (LPD) is performed by top-hat transformation, vertical edge detection, morphological operations, and various validations. Then, character-specific ERs are extracted as character regions in license plate candidates. Followed by suitable selection of ERs, the segmentation of characters and coarseto- fine LPD are achieved simultaneously. Finally, an offline trained pattern classifier of HDRBM is applied to recognize the characters. The proposed method is robust to illumination changes and weather conditions during 24 h or one day. Experimental results on thorough data sets are reported to demonstrate the effectiveness of the proposed approach in complex traffic environments.

关键词： License plate detection license plate recognition hybrid discriminative restricted Boltzmann machines extremal regions

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A Multi-view Learning Approach to Foreground Detection for Traffic Surveillance Applications

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2016年第6期65卷 4144-4158页

作者： Wang, Kunfeng Liu, Yuqiang Gou, Chao Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China China Acad Railway Sci Beijing 100081 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Natl Univ Def Technol Res Ctr Computat Expt & Parallel Syst Changsha 410073 Hunan Peoples R China

This paper proposes an effective multi-view learning approach to foreground detection for traffic surveillance applications. This approach involves three main steps. First, a reference background image is generated via temporal median filtering, and multiple heterogeneous features (including brightness variation, chromaticity variation, and texture variation, each of which represents a unique view) are extracted from the video sequence. Then, a multi-view learning strategy is devised to online estimate the conditional probability densities for both the foreground and the background. The probability densities of three features are approximately conditionally independent and are estimated with kernel density estimation. Pixel soft lab.ling is conducted by using Bayes rule, and the pixelwise foreground posteriors are computed. Finally, a Markov random field is constructed to incorporate the spatiotemporal context into the foreground/background decision model. The belief propagation algorithm is used to lab.l each pixel of the current frame. Experimental results verify that the proposed approach is effective to detect foreground objects from challenging traffic environments and outperforms some state-of-the-art methods.

关键词： Conditional independence foreground detection heterogeneous features Markov random field (MRF) multi-view learning

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Parameter identification of plant growth models with stochastic development

Parameter identification of plant growth models with stochas...

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IEEE International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications (FSPMA)

作者： Kang Mengzhen Hua Jing de Reffye, Philippe Jaeger, Marc CASIA LIAMA State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Sci Qingdao Peoples R China CIRAD AMAP Unit F-34398 Montpellier France Univ Montpellier LIRMM ICAR F-34095 Montpellier France

ISBN: (纸本)9781509016594

Plant architectures generally display structural variations among individuals. Stochastic FSPMs have been developed to capture such feature, but calibrating such models is a challenging issue. For Greenlab.model, parameter identification has been achieved on several crops and trees, but the estimation of functional parameters is mostly limited to plants with deterministic development. In this work, we propose a methodological framework allowing the efficient FSPM parameter estimation for stochastic ramified plants. We focus on the randomness in three kinds of meristem activities in plant development: growth, death and branching. Concepts of organic series and potential structure are introduced to build the fitting target as well as corresponding model output. We show that, with a limited set of sampled plants (here from simulation), using a few organic series, the inverse method retrieves well the parameter values (the original parameter set being known here). Requiring the concept of physiological age and the assumption of common biomass pool, the proposed approach provides a solution of solving source-sink functions of complex plant architectures, with a novel simplified way of plant sampling. The proposed parameter estimation frame is promising, since this in silico process mimics the procedure of calibrating model for real plants in a stand. Estimating parameters on stochastic plant architectures opens a new range of coming applications.

关键词： Greenlab inverse method source-sink parameters functional-structural plant model stochastic development parameter estimation in silico

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Where Does AlphaGo Go: From Church-Turing Thesis to AlphaGo Thesis and Beyond

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IEEE/CAA Journal of Automatica Sinica 2016年第2期3卷 113-120页

作者： Fei-Yue Wang Jun Jason Zhang Xinhu Zheng Xiao Wang Yong Yuan Xiaoxiao Dai Jie Zhang Liuqing Yang IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences (SKL-MCCS CASIA) Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology the Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver the Department of Computer Science and Engineering University of Minnesota the Qingdao Academy of Intelligent Industries (QAII) Qingdao Shandong China and SKL-MCCS CASIA the Department of Electrical and Computer Engineering Colorado State University

An investigation on the impact and significance of the AlphaGo vs. Lee Sedol Go match is conducted, and concludes with a conjecture of the AlphaGo Thesis and its extension in accordance with the Church-Turing Thesis in the history of computing. It is postulated that the architecture and method utilized by the AlphaGo program provide an engineering solution for tackling issues in complexity and intelligence. Specifically, the AlphaGo Thesis implies that any effective procedure for hard decision problems such as NP-hard can be implemented with AlphaGo-like approach. Deep rule-based networks are proposed in attempt to establish an understandable structure for deep neural networks in deep learning. The success of AlphaGo and corresponding thesis ensure the technical soundness of the parallel intelligence approach for intelligent control and management of complex systems and knowledge automation. © 2014 Chinese Association of Automation.

关键词： Religious buildings

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Performance Evaluation of the Deep Learning Approach for Traffic Flow Prediction at Different Times

Performance Evaluation of the Deep Learning Approach for Tra...

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IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

作者： Duan, Yanjie Lv, Yisheng Wang, Fei-Yue Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat Beijing Engn Res Ctr Intelligent Syst & Technol Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Shandong Peoples R China

ISBN: (纸本)9781509029273

Traffic flow prediction is very important in the deployment of intelligent transportation system. Based on our previous research on deep learning approach for traffic data prediction, we further evaluates the performance of the SAE model for traffic flow prediction at daytime and nighttime. Through 250 experimental tasks training a SAE model and evaluating its performance at daytime and nighttime with 3 different criteria, we obtain the best combination of hyper parameters for each criterion at different times on weekday and non-weekday, respectively. Experimental results show that the MAE and RMSE at daytime are larger than that at nighttime, while the MRE at daytime are smaller than that at nighttime. For different criteria, the hyper parameters of the SAE model should vary accordingly. The results in this paper indicate that in real applications, traffic flow prediction using the deep learning approach can be a combination of multiple SAE models with different parameters suitable for different periods, which is of significance in future research.

关键词： Forecasting

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Identification for Switched systems

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IFAC-PapersOnLine 2015年第28期48卷 514-519页

作者： Hu, Qiong Fei, Qing Ma, Hongbin Wu, Qinghe Geng, Qingbo State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

For a class of unstable discrete-time multi-variable switched systems with parametric uncertainty, an identification scheme is developed in this paper. Specifically, the identification algorithm is derived to identify the parameter vectors of potential subsystems based on the idea of least geometric mean squares. Furthermore, an neural network classifier is put forward for partition of the identified subsystems. Finally, feasibility and effectiveness of the proposed identification scheme are verified by numerical simulations, which show that the desirable identification performance is guaranteed with the proposed scheme. © 2015

关键词： Parameter estimation Computational fluid dynamics Geometric mean Identification algorithms Identification scheme Multi variables Neural network classifier Parameter vectors Parametric uncertainties Switched system

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An overall solution of Virtual Reality Classroom

An overall solution of Virtual Reality Classroom

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Xisong Dong The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Institute of Smart Education Systems Qingdao Academy of Intelligent Industries

Virtual Reality(VR) is a three-dimensional computergenerated virtual world. It is essential to introduced VR technology to education area to develop new teaching mode to improve the efficiency and quality of teaching and learning. Among them, VR classroom has quickly become most dazzling star with its subversive advantage. This paper proposes an overall integration solution of VR classroom, including its composition, its scene design of various disciplines and its main advantage. Finally, a case study of a geography lesson is provided to show its advantages and strong potentiality.

关键词： Virtual Reality Education virtual classroom

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How to “STEAM” Children at Home? Let Children “STEAM” Themselves

How to “STEAM” Children at Home? Let Children “STEAM” Th...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Xiaoyan Gong The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Institute of Smart Education Systems Qingdao Academy of Intelligent Industries

In this article, I would like to share my daughter's experience on self-STEAM education. In our daily life, she can always find problems and then dream them with her imagination, finally narrows down her solutions to solve problems in her own way. During these problem-solving processes, I noticed that she went through sciences, technology, engineering, arts and mathematics in a very natural way. So I would like to say, STEAM is the way we learn and grow ever since we were born. But later at school, we are trained in a way that subjects are completely disconnected. It might take time to change this situation at school, but at home, as parents, we need to realize that children can discover new things by themselves even from young ages, and provide rich learning environment for them and let them "STEAM " themselves in their own way.

关键词： STEM STEAM education maker education

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A Simple and Effective Method For the Use of Chemical Accident Cases

A Simple and Effective Method For the Use of Chemical Accide...

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IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

作者： Jing, Sifeng Liu, Xiwei Xu, Chuanzhong Qingdao Acad Intelligent Ind Inst Smart Educ Syst Qingdao Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China PetroChina Fushun Petrochem Co Refinery 2 Fushun Peoples R China

ISBN: (纸本)9781509029273

past chemical industry accident cases include volume valuable information like precursor, equipment involved, relevant causes and experiences of emergence response. In-depth analysis and fully utilization of these information play an important decision-making role in controlling risk and enhancing safety performance in chemical industry. In this work, a survey of use of accident data is conducted around the world and the result shows that the detailed use of these information play an important role in preventing accidents. However, in china there much more needs to be done in the application of accident data. According to the needs of safety management of chemical plants, a simple and effective method of the use of chemical accident cases is proposed based on collecting and analyzing of a large number of chemical accident cases. And finally, a utilization system of chemical industry accident cases is implemented through Microsoft access 2010. The result shows that the system can realize the effective management and use of past chemical accident information.

关键词： chemical accident cases use of information database fuzzy query chemical safety performance

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Robust traffic sign detection in complex road environments

Robust traffic sign detection in complex road environments

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IEEE International Conference on Vehicular Electronics and Safety (ICVES)

作者： Bin Tian Ran Chen Yanjie Yao Naiqiang Li State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (纸本)9781509029341

Traffic sign recognition is an important topic in driver assistant system and intelligent autonomous vehicles. Traffic sign detection is a critical step, whose performance greatly affect the performance and computation cost of traffic sign recognition. In this paper, we propose a traffic sign detection method based on a scoring SVM model. First, traffic sign color and color gradient are extracted according to their color characteristics. Then, the shape of traffic sign is computed by a voting scheme, yielding shape score maps. After that, the score maps of traffic signs are used to train a SVM model. Compared with single traffic sign score value, the score map is more efficient to verify the existence of a traffic sign. Finally, the trained SVM model is used to detect traffic signs. Experiments show that the proposed method is more effective than the voting based method to detect traffic signs.

关键词： Support vector machines Decision support systems Color Image edge detection Erbium Shape Detectors

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