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IEEE International Conference on Applied Superconductivity and Electromagnetic Devices

作者： Yu Ping Zhang Yi Mou Zhong Xiao Yang Yu Hua Wei Tao Liu Dong Chen Pattern Recognition and Intelligent Control Laboratory University of Electronic Science and Technology of China

ISBN: (纸本)9781467381086

Aluminum air fuel cell has several characters as a kind of new energy, such as large specific energy, rich fuel source, low environmental pollution and so on. The character of high specific energy could extend driving range of electric vehicle, but a low specific power with aluminum air fuel cell demands it should cooperate with lithium ion battery and super capacitor, which export higher power to drive the electronic vehicle. As a rechargeable power supply, lithium ion battery and super capacitor can effectively recycle energy at braking mode, so that they can step to extend driving range.

关键词： Aluminum air fuel cell Specific energy Specific power Lithium ion battery Super capacitor Recycle energy

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Detection of billet character in complex production line scene

Detection of billet character in complex production line sce...

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2012 3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012

作者： Hong, Hanyu Yu, Zhejun Zhang, Xiuhua Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430205 China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769547725

Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmented method can be used in a wide variety of billet scenes. According to high temperature and complex scene in the rolling line, we use an effective clustering and projection characteristics to determine the terminal condition of recursive segmentation. Then we can label character candidate regions in turn by this effective characteristics, and select the regions we want to achieve. The experiments show that this method makes full use of the characteristics of region and clustering. It can improve the quality of detection, and the detection result meets the need of practical application. © 2012 IEEE.

关键词： CCD cameras

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Fitting a functional structural plant model based on global sensitivity analysis

Fitting a functional structural plant model based on global ...

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2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012

作者： Lin, Yubin Kang, Mengzhen Hua, Jing National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467304283

Calibration of a functional structural plant model is a challenging task because of the complexity of model structure. Parameter estimation through gradient-based optimization technique was highly dependent on initial parameter values. This motivated the use of global sensitivity analysis technique to choose parameter subset in fitting the data sequence. Global sensitivity indices were computed using the source sink ratio as the output of interest, which regulates all organ growth. By fitting on chrysanthemum data from nine sampling dates, it is shown that sensitivity analysis method helps to identify the influential parameters for a given sampling date. As a result, fitting process is less dependent on the initial parameter values. Current work provides a new method of calibrating a plant growth model with multiple outputs. © 2012 IEEE.

关键词： Sensitivity analysis

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Detection of Billet Character in Complex Production Line Scene

Detection of Billet Character in Complex Production Line Sce...

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第三届数字制造与自动化国际会议

作者： Hong Hanyu Yu Zhejun Zhang Xiuhua Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

关键词： image processing production line billet character

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Detection of Billet Character in Complex Production Line Scene

Detection of Billet Character in Complex Production Line Sce...

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International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Hong Hanyu Yu Zhejun Zhang Xiuhua Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan China

关键词： Billets Image segmentation Steel Arrays Filtering Licenses

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Computation of the folkman number Fv(3,5;6)

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Journal of Combinatorial Mathematics and Combinatorial Computing 2012年 81卷 11-17页

作者： Shao, Zehui Liang, Meilian Pan, Linqiang Xu, Xiaodong School of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing China School of Mathematics and Information Science Guangxi University Nanning 530004 China Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Guangxi Academy of Sciences Nanning Guangxi 530007 China

We prove that Fv(3,5;6) = 16, which solves the smallest open case of vertex Folkman numbers of the form Fv(3,k;k + 1). The proof uses computer algorithms.

关键词： Mathematical techniques

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An image matching evolutionary algorithm based on Hu invariant moments

An image matching evolutionary algorithm based on Hu invaria...

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3rd International Conference on Image Analysis and Signal Processing, IASP 2011

作者： Zhang, Ruliang Wang, Lin Key Laboratory of Pattern Recognition and Intelligent Control Guizhou University for Nationalities Guiyang China

ISBN: (纸本)9781612848808

This paper presents an image matching evolutionary algorithm (called IMEA algorithm) based on Hu invariant moments. First, the population is initialized. A group of searched subgraphs is constructed. Second, the fitness function based on Hu invariant moments is designed. The seven Hu invariant moments of the template image and the searched subgraph are calculated. The Euclidean distance of Hu invariant moments is used to measure similarity between the template image and the searched subgraph. The template image and the searched subgraph are matched if these Euclidean distances are less than the set threshold. Finally, a new searched subgraph is constructed by means of a new evolutionary strategy. The new searched subgraph replaces the searched subgraph whose value of the fitness function is maximum. Experimental results demonstrate the great robustness and efficiency of the IMEA algorithm. © 2011 IEEE.

关键词： Evolutionary algorithms

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Fitting a Functional Structural Plant Model based on Global Sensitivity Analysis

Fitting a Functional Structural Plant Model based on Global ...

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IEEE International Conference on Automation Science and Engineering

作者： Yubin LIN Mengzhen KANG Jing HUA National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467304290

Calibration of a functional structural plant model is a challenging task because of the complexity of model structure. Parameter estimation through gradient-based optimization technique was highly dependent on initial parameter values. This motivated the use of global sensitivity analysis technique to choose parameter subset in fitting the data sequence. Global sensitivity indices were computed using the source sink ratio as the output of interest, which regulates all organ growth. By fitting on chrysanthemum data from nine sampling dates, it is shown that sensitivity analysts method helps to identify the influential parameters for a given sampling date. As a result, fitting process is less dependent on the initial parameter values. Current work provides a new method of calibrating a plant growth model with multiple outputs.

关键词： Sensitivity analysis plant models organ growth MACHINE SHOP PRACTICE

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An Image Matching Evolutionary Algorithm Based on Hu Invariant Moments

An Image Matching Evolutionary Algorithm Based on Hu Invaria...

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2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

作者： Ruliang Zhang Lin Wang Key Laboratory of Pattern Recognition and Intelligent Control Guizhou University for NationalitiesGuiyang China

ISBN: (纸本)9781612848792

关键词： Hu invariant moments evolutionary algorithm euclidean distance image matching

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Video vehicle detection through multiple background-based features and statistical learning

Video vehicle detection through multiple background-based fe...

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International Conference on intelligent Transportation

作者： Mingxia Sun Kunfeng Wang Ming Tang Fei-Yue Wang Jinfeng Yang Tianjin Key Laboratory of Advanced Signal Processing Civil Aviation University of China Tianjin China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences (CAS) Beijing China

This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image, assuming moving vehicles may cause pixel intensities and local texture to change, and then by identifying such pixel changes to detect vehicles. In this research, multiple pattern classifiers including LDA + Adaboost, SVM, and Random Forests are used to detect vehicles that are passing through virtual loops. We extract fourteen pattern features (related to foreground area, texture change, and luminance and contrast in the local virtual loop zone and the global image) to train pattern classifiers and then detect vehicles. As experimental results illustrate, the proposed approach is quite robust to detect vehicles under complex dynamic environments, and thus is able to improve the accuracy of traffic data collection in all weather for long term.

关键词： Vehicles Feature extraction Training Image edge detection Vehicle detection Meteorology Radio frequency

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