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检索条件"任意字段=Image Processing: Algorithms and Systems XI"

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Quantum-inspired evolutionary multicast algorithm

Quantum-inspired evolutionary multicast algorithm

引用

IEEE International Conference on systems, Man and Cybernetics

作者： Yangyang Li Licheng Jiao Jingjing Zhao Qiuyi Wu Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

As a global optimizing algorithm, genetic algorithm (GA) is applied to solve the problem of multicast more and more. GA has more powerful searching ability than traditional algorithm, however its property of ¿prematurity¿ makes it difficult to get a good multicast tree. A quantum-inspired evolutionary algorithm (QEA) to deal with multicast routing problem is presented in this paper, which saliently solves the ¿prematurity¿ problem in genetic based multicast algorithm. Furthermore, in QEA, the individuals in a population are represented by multistate gene quantum bits and this representation has a better characteristic of generating diversity in population than any other representations. In the individual's updating, the quantum rotation gate strategy is applied to accelerate convergence. The algorithm has the property of simple realization and flexible control. The simulation results show that QEA has a better performance than CS and conventional GA.

关键词： Multicast algorithms Competitive intelligence Laboratories Information processing Evolutionary computation Routing Genetic algorithms Quality of service Quantum computing Heuristic algorithms

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Construction of Filter Banks of Biorthogonal Vector-valued Compactly Supported Wavelets with Three-Scale

Construction of Filter Banks of Biorthogonal Vector-valued C...

引用

GCIS, WRI Global Congress on Intelligent systems

作者： Qingjiang Chen Ping-An Wang School of Science Xi'an University of Architecture and Technology Xi'an China

Wavelet analysis has become a popular subject in scientific research for twenty years. It has been a powerful tool for exploring and solving many complicated problems in natural science and engineering computation. In this paper, the notion of vector-valued multiresolution analysis is introduced and the definition of the biorthogonal vector-valued wavelets is given. The existence of biorthogonal vector-valued wavelets associated with a pair of biorthogonal vector-valued compactly supported scaling functions is investigated. An algorithm for constructing a class of biorthogonal vector-valued compactly supported wavelet functions is presented by virtue of multiresolution analysis and matrix theory.

关键词： Filter bank Wavelet analysis Multiresolution analysis Discrete wavelet transforms Hydrogen Intelligent systems Power engineering and energy Power engineering computing Signal processing algorithms image coding

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A Parallel Artificial Immune Model for Optimization

A Parallel Artificial Immune Model for Optimization

引用

International Conference on Computational Intelligence and Security

作者： Yutao Qi Fang Liu Licheng Jiao School of Computer Science And Technology Key Laboratory of Intelligent Perception and Imagee Understanding of Ministry of Education Xidian University Xi'an China Institute of Intelligent Information Processing and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China

This paper presents a parallel artificial immune model termed as tower master-slave model (TMSM) for solving optimising problems. Based on TMSM, the parallel immune memory clonal selection algorithm (PIMCSA) is also proposed. TMSM is a two level coarse-grained parallel artificial immune model with distributed immune response and distributed immune memory. In PIMCSA, vaccines are extracted and migrated between populations rather than individual migration as has been done in parallel genetic algorithms. It is a good balance between population diversity and the convergent speed. Experimental results on the numerical optimization and TSP problems show that PIMCSA achieves good performance in terms of both solution quality and computation time.

关键词： Immune system Genetic algorithms Artificial immune systems Competitive intelligence Master-slave Laboratories Computer science education Poles and towers Vaccines Parallel processing

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An Algorithm of Feature Selection and Feature Weighting Adjustment Based on Chinese FrameNet

An Algorithm of Feature Selection and Feature Weighting Adju...

引用

Congress on image and Signal processing, CISP

作者： Xu Zhao xi Liu xiaoyan Hao Kaiying Liu Academe of Computer & Software Engineering Taiyuan University of Technology Taiyuan China School of Computer & Information Technology Shanxi University Taiyuan China

The combination of TF and DF, which is used as the method of feature selection, and TF-EDF algorithm, which is used as feature weighting, are frequently used in the text categorization. But for a small training set, the combination of TF and DF will filter out many low-frequency words which have a strong capability of the feature discrimination. Hence the weight is directly influenced. In this paper, an algorithm of feature selection and feature weighting adjustment based on Chinese FrameNet (CFN) are presented which aims at solving the problem mentioned above. The experimental result indicates that the precision which is greater than the traditional algorithm can reach to 67.3% and can fits the small training set very well.

关键词： Spatial databases Text categorization Frequency Software algorithms Large-scale systems Layout Software engineering Information technology Filters Statistics

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Clustering-based selection for evolutionary multi-objective optimization

Clustering-based selection for evolutionary multi-objective ...

引用

IEEE International Conference on Intelligent Computing and Intelligent systems (ICIS)

作者： Maoguo Gong Licheng Jiao Gang Cheng Chao Liu Key Laboratory of Intelligent Perception and Image Institute of Intelligent Information Processing Xidian University Xi'an China

ISBN: (纸本)9781424447374;9781424447541

In this study, a novel clustering-based selection strategy of nondominated individuals for evolutionary multi-objective optimization is proposed. The new strategy partitions the nondominated individuals in current Pareto front adaptively into desired clusters. Then one representative individual will be selected in each cluster for pruning nondominated individuals. In order to evaluate the validity of the new strategy, we apply it into one state of the art multi-objective evolutionary algorithm. The experimental results based on thirteen benchmark problems show that the new strategy improves the performance obviously in terms of breadth and uniformity of nondominated solutions.

关键词： Genetic algorithms Evolutionary computation Information processing Sorting Chaos Nearest neighbor searches Particle swarm optimization Design optimization

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image Denoising Algorithm Using Adaptive Shrinkage Threshold Based on Shearlet Transform

Image Denoising Algorithm Using Adaptive Shrinkage Threshold...

引用

Japan-China Joint Workshop on Frontier of Computer Science and Technology (FCST)

作者： xi Chen Hui Sun Chengzhi Deng Department of Computer Science & Technology Nanchang Institute of Technology Nanchang China

Threshold selection is the critical issue in image denoising. This paper deal with a new multiscale directional representation called the shearlet transform that has shown to represent specific classes of images with distributed discontinuities optimally. Techniques based on this transform for denoising using an efficient adaptive shrinkage threshold are presented. The shearlet transform not only provides the mean to detect orientations and to lead to sparse representations, but is moreover equipped with a rich mathematical structure similar to wavelets. Experiments show that this novel approach is very competitive for the purpose of image denoising.

关键词： image denoising Wavelet transforms Continuous wavelet transforms Multidimensional systems Noise reduction Computer science Wavelet analysis Signal processing algorithms Sun Digital filters

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Airborne moving vehicle detection for video surveillance of urban traffic

Airborne moving vehicle detection for video surveillance of ...

引用

IEEE Symposium on Intelligent Vehicle

作者： Renjun Lin xianbin Cao Yanwu Xu Changxia Wu Hong Qiao Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei China University of Manchester Institute of Science and Technology UK Institute of Automation Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424435036

Urban traffic surveillance, which is designed to improve traffic management, is an important part of intelligent traffic system (ITS). In particular, airborne moving vehicle detection has become a new but hot research area since its wide view and low cost. However, airborne urban traffic surveillance is impacted by many difficulties such as camera vibration, vehicle congestion, background variance, serious thermal noise etc. Therefore, image subtraction and thermal image processing have low detection rate, while the optical flow method cannot meet the real-time application. In this paper, we propose a coarse-to-fine method, which can be divided into two stages of pre-processing and classification inspection. In pre-processing stage, the candidates regions of moving vehicle are obtained by employing Road Detection, Removal of Non-vehicle Regions and Moving Regions Extraction. The speed of this stage is fast but there is still relatively high false-positive-rate. In classification inspection stage, a well-trained cascade classifier, which refines the candidate regions, is designed to maintain a higher detection rate and a lower false alarm rate. Experimental results demonstrate that compared with representative algorithms, our method reach better performance in detection rate and false-positive-rate, while meeting the needs of real-time application.

关键词： Vehicle detection Video surveillance Optical noise Inspection Intelligent systems Costs Cameras Vehicles Background noise image processing

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Tracking multiple objects using particle filters and digital elevation maps

Tracking multiple objects using particle filters and digital...

引用

IEEE Symposium on Intelligent Vehicle

作者： Radu Danescu Florin Oniga Sergiu Nedevschi Marc-Michael Meinecke Computer Science Department Technical University of Cluj Napoca Cluj-Napoca Romania Driving Assistance Electronics Department Volkswagen AG Germany

ISBN: (纸本)9781424435036

Tracking multiple objects has always been a challenge, and is a crucial problem in the field of driving assistance systems. The particle filter-based trackers have the theoretical possibility of tracking multiple hypotheses, but in practice the particles will cluster around the stronger one. This paper proposes a two-level approach to the multiple object tracking problem. One particle filter-based tracker will search the whole state space for new hypotheses, and when a hypothesis becomes strong enough, it will be passed to an individual object tracker, which will track it until the object is lost. The initialization tracker and the individual object trackers use the same state models and the same measurement technique, based on stereovision-generated elevation maps, and differ only in their use of the estimation results. The proposed solution is a simple and robust one, adaptable to different types of object models and to different types of sensors.

关键词： Particle tracking Particle filters image edge detection Stereo image processing Probability density function State-space methods Computer science Filtering Detection algorithms image reconstruction

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Hybrid multiobjective estimation of distribution algorithm by local linear embedding and an immune inspired algorithm

Hybrid multiobjective estimation of distribution algorithm b...

引用

Congress on Evolutionary Computation

作者： Dongdong Yang Licheng Jiao Maoguo Gong Hongxiao Feng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

A novel hybrid multiobjective estimation of distribution algorithm is proposed in this study. It combines an estimation of distribution algorithm based on local linear embedding and an immune inspired algorithm. Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise continuous (m-1)-dimensional manifold, where m is the number of objectives. By this regularity, a local linear embedding based manifold algorithm is introduced to build the distribution model of promising solutions. Besides, for enhancing local search ability of the EDA, an immune inspired sparse individual clone algorithm (SICA) is introduced and combined with the EDA. The novel hybrid multiobjective algorithm, named HMEDA, is proposed accordingly. Compared with three other state-of-the-art multiobjective algorithms, this hybrid algorithm achieves comparable results in terms of convergence and diversity. Besides, the tradeoff proportions of EDA to SICA in HMEDA are studied. Finally, the scalability to the number of decision variables of HMEDA is investigated too.

关键词： Electronic design automation and methodology Machine learning algorithms Probability distribution Evolutionary computation Cloning Hybrid power systems Genetic mutations Genetic algorithms Sampling methods Principal component analysis

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Scene matching based on spatial relation constraint in suitable-matching area

Scene matching based on spatial relation constraint in suita...

引用

IEEE International Conference on Intelligent Computing and Intelligent systems (ICIS)

作者： Yaojun Li Ying Yu Quan Pan Chunhui Zhao School of Automation Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781424447374;9781424447541

Scene matching navigation system (SMNS) is one of the most effective ways of aided navigation for UAV. With anti-electronic interference and high resolution, SMN could be navigating and locating reliably and accurately. The navigational positioning ability with high reliability and high accuracy must be needed. For the complexity of the work environment of scene matching navigation on the platform of UAV, a multi-region scene matching algorithm for suitable-matching area based on the spatial relation constraint was proposed in this paper. This algorithm adopts parallel computing to improve the real-time performance of SMNS. The optimal allocation of coordinates of center point can be estimated ultimately by calculating the spatial relation of many match areas. So the precise location of real-time image center at the base map can be gotten. At last, a method based on previous navigation data was designed to check the location. To accomplish the on-line scene matching reliably and precisely, this algorithm only needs one real-time frame image to match base map every time. Experiments show that this algorithm meets the UAV navigation performance requirements such as real-time, robustness and high accuracy.

关键词： Layout Unmanned aerial vehicles Global Positioning System Aircraft navigation Automation Robustness Interference Spatial resolution Parallel processing Clustering algorithms

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