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International Conference on Pattern Recognition

作者： Xiaopeng Hong Hong Chang Xilin Chen Wen Gao School of Computer Science and Technology Harbin Institute of Technology China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China Institute of Digital Media Peking University China

ISBN: (纸本)9781424475421

This paper presents a new method to detect pedestrian in still image using Sigma sets as image region descriptors in the boosting framework. Sigma set encodes second order statistics of an image region implicitly in the form of a point set. Compared with the covariance matrix, the traditional second order statistics based region descriptor, which requires computationally demanding operations based on Riemannian manifold, Sigma set preserves similar robustness and discriminative power more efficiently because the classification on Sigma sets can be directly performed in vector space. Experimental results on the INRIA and the Daimler Chrysler pedestrian datasets show the effectiveness and efficiency of the proposed method.

关键词： Classification algorithms Manifolds Detectors Feature extraction Training Covariance matrix Support vector machine classification

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Image Fusion Based on NSCT and Fuzzy Logic

Image Fusion Based on NSCT and Fuzzy Logic

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International Conference on Multimedia technology

作者： Xianyi Ren Yijun Zheng Tao Hu Jihong Zhang Shenzhen Key Laboratory of Visual Media Processing and Transmission Shenzhen Institute of Information Technology Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

Nonsubsampled contourlet transform (NSCT) can provide flexible multiresolution, anisotropy, and directional expansion for images. Compared with the original contourlet transform, it is shift-invariant and can overcome the pseudo-gibbs phenomena around singularities. Fuzzy logic is an efficient intelligent method to handle uncertain information. In this paper, a novel image fusion algorithm is proposed based on the NSCT and fuzzy logic. Extensive experiments show that the proposed method can improve subjective and objective results compared to some other fusion approaches.

关键词： Fuzzy logic Image fusion Algorithm design and analysis Discrete wavelet transforms Fuzzy sets

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Novel Quality Measures for Image Fusion Based on Structural Similarity and Visual Attention Mechanism

Novel Quality Measures for Image Fusion Based on Structural ...

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International Conference on Multimedia technology

作者： Xianyi Ren Xiujian Liu Tao Hu Jihong Zhang Shenzhen Key Laboratory of Visual Media Processing and Transmission Shenzhen Institute of Information Technology Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

A novel objective quality for image fusion based on structural similarity and visual attention mechanism (VAM) is presented. By giving higher weight to the salient areas in the input images, the quality measure can estimate how much visual meaningful information is preserved in the fused image. The correlation analysis between objective measure and subjective evaluation showed that our measures are more consistent with human subjective evaluation.

关键词： Visualization Image fusion Humans Correlation Indexes Q measurement

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Neural network predictive control of vehicle suspension

Neural network predictive control of vehicle suspension

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International Conference on information Science and Engineering (ICISE)

作者： Jing Xu Juntao Fei College of Computer and Information Hohai University HHU Changzhou China Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology Hohai University HHU Changzhou China

Smooth traveling and comfort ride are the basic evaluation criterions for a ground vehicle. This paper attempts to establish the vibration control technology based on neural network predictive control, use these predicted values to determine control input to optimize the future performance of the vehicle and improve the smooth and comfort ride of vehicle. The dynamic model of vehicle suspension system is discussed, and the linear passive suspension model and nonlinear spring suspension model of the vertical acceleration are compared. Because of the great advantages of the neural network in dealing with the nonlinear property of the spring suspension system, a BP neural network predictive controller is designed and implemented to predict the vertical acceleration of the vehicle suspension system. Simulations demonstrate the effectiveness of the neural network predictive controller with application to vehicle system.

关键词： Suspensions Artificial neural networks Vehicles Predictive control Predictive models Springs Acceleration

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Adaptive mutation particle filter based on diversity guidance

Adaptive mutation particle filter based on diversity guidanc...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jin-Xia Yu Yong-Li Tang Wen-Jing Liu College of Computer Science and Technology Henan Polytechnic University Jiaozuo China Jiangsu Provincial Key Laboratory of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing China Department of Computer Science and Technology Tsinghua University Beijing China

Aimed at the deficiency of the resampling algorithm in PF, diversity measures ESS (effective sample size) and PDF (population diversity factor) are evaluated respectively. Combined with the estimation result, diversity measures PDF is used for adaptively tuning the resampling threshold. By integrating the operation of particle mutation after resampling into PF and using the above mechanism of diversity guidance, the AMPF algorithm (Adaptive Mutation PF) is presented so as to assure the diversity of particle sets. With the simulation program using matlab 7.0 to track a single target motion from a fixed visual observation points, the performance of diversity measures and AMPF are evaluated and the validity of the proposed method is verified.

关键词： Particle measurements Atmospheric measurements Particle filters Algorithm design and analysis Mathematical model Tuning Estimation

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A distributed approach to consistent order delivery of concurrent events in asynchronous DVEs

ICETC 2010 - 2010 2nd International Conference on Education ...

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ICETC 2010 - 2010 2nd International Conference on Education technology and computer 2010年 4卷 V495-V498页

作者： Zhou, Hangjun Zhang, Wei Peng, Yuxing Li, Sikun Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha Hunan 410073 China Department of Information Management Hunan College of Finance and Economics Changsha Hunan 410205 China

ISBN: (纸本)9781424463688

In large-scale asynchronous distributed virtual environments(DVEs), one of the difficult problems is to deliver the concurrent events in a consistent order at each node. Generally, the previous consistency control approaches can be classified into two categories: causal order and time stamped order. However, causal order approaches can merely preserve the cause-effect relation of events and time stamped order approaches seem intrinsically complex to be used in serverless large-scale asynchronous DVEs. In this paper, we proposed a novel distributed algorithm to identify the concurrent events and preserve the consistent order delivery of them at different nodes. Simulation studies are also carried out to compare the performance of this algorithm with that of the previous ones. The results show that the new algorithm can effectively deliver the concurrent events in consistent order at each node and is more efficient than the previous algorithms in large-scale asynchronous DVEs. © 2010 IEEE.

关键词： Virtual reality

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Multi-mode bandstop filter using defected equilateral triangular patch resonator

Multi-mode bandstop filter using defected equilateral triang...

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Jian-Kang Xiao Xiao-Peng Zu Hui-Fen Huang Wei-Li Dai Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology Changzhou China School of Computer and Information Hohai University Changzhou China School of Computer and Information Hohai University Changzhou Changzhou China School of Electronic and Information Engineering South China University of Technology Guangzhou Guangzhou China

Microstrip multi-band bandstop filters using tri-mode equilateral triangular patch resonator are developed, and the rules of resonant frequency and patch defection dimension are obtained by calculation. With fractal patch defection and a higher substrate permittivity, higher order modes of resonator are activized for the multi-band implementation, and the dominant mode TM 1,0,-1 , and the higher order modes TM 1,1,-2 and TM 2,-2,0 are fully applied, and filter performances are greatly enhanced. The design is demonstrated by experiment. The proposed filters have advantages of simple topology, compact size and nicer performances, and all these features are well popular for wireless communication systems.

关键词： Resonant frequency Fractals Manganese

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A HSC-based sample selection method for support vector machine

A HSC-based sample selection method for support vector machi...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qing He Ning Li Zhong-Zhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding Hebei China Chinese Academy and Sciences China

Support Vector Machine (SVM) is a classification technique of machine learning based on statistical learning theory. A quadratic optimization problem needs to be solved in the algorithm, and with the increase of the samples, the time complexity will also increase. So it is necessary to shrink training sets to reduce the time complexity. A sample selection method for SVM is proposed in this paper. It is inspired from the Hyper surface classification (HSC), which is a universal classification method based on Jordan Curve Theorem, and there is no need for mapping from lower-dimensional space to higher-dimensional space. The experiments show that the algorithm shrinks training sets keeping the accuracy for unseen vectors high.

关键词： Support vector machines Training Classification algorithms Machine learning Accuracy Testing Machine learning algorithms

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An Image-Sequence Compressing Algorithm Based on Homography Transformation for Unmanned Aerial Vehicle

An Image-Sequence Compressing Algorithm Based on Homography ...

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International Symposium on Intelligence information processing and Trusted Computing (IPTC)

作者： Junbin Gong Chenlin Zheng Jinwen Tian Dingxue Wu Institute for Pattern Recognition and Artificial Intelligence National key laboratory of science and technology on multi-spectral information processing Huazhong University of Science and Technology Wuhan China College of Computer Science and Technology Huanggang Normal University Huangang China

Focus on the image compressing problem of unmanned aerial vehicle with high compression ratio, fixed compressing ratio and low computational complexity requirement, a low-complexity image-sequence compressing algorithm based on homography transformation was proposed. The image sequences were dynamically divided into frame-groups according the data from airborne inertial navigation systems, and the intermediate frames in the same frame-group was b i-directionally predicted by the first-frame and the end-frame with homography transformation. The homography matrix was got approximately by the airborne inertial navigation systems firstly and then was accurately computed by fast multiple sub-areas template matching. At the end the first frame and the residual images of the intermediate frames of the same frame-group was merged into a big image and coded by JPEG2000 to generate fixed-size code streams. The experiment results show that the proposed algorithm was with high compression performance, low computational complexity and excellent capacity for code-size control and will has good prospect in engineer.

关键词： Image coding Unmanned aerial vehicles Cameras Transform coding Image restoration Image sequences Heuristic algorithms

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Predicting RNA secondary structure with Tabu Search

Predicting RNA secondary structure with Tabu Search

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IEEE International Conference on Cognitive Informatics

作者： Yongguo Liu Jianrui Hao Jun Peng Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University Xiangtan China School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China College of Electronic Information Engineering Chongqing University of Science and Technology Chongqing China

In this paper, a novel method for predicting RNA secondary structure called RNA secondary structure prediction based on Tabu Search (RNATS) is proposed. In RNATS, two search models, intensification search and diversification search, are designed to exploit the local regions around the current solution and explore the unvisited space, respectively. Simulation experiments are conducted for six RNA sequences to show that the proposed method is feasible and effective.

关键词： RNA computer simulation Space exploration Neodymium Nickel Laboratories

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