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Congress on Evolutionary Computation

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

Based on the theory of clonal selection in immunology, by introducing Baldwin effect, an improved clonal selection algorithm, termed as Baldwin clonal selection algorithm (BCSA), is proposed to solve the optimal approximation of linear systems. For engineering computing, the novel algorithm adopts three operations to evolve and improve the population: clonal proliferation operation, Baldwinian learning operation and clonal selection operation. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new algorithm have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm, multi-agent genetic algorithm and artificial immune response algorithm.

关键词： Evolutionary computation

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MULTI-ROBOT TRACKING OF MOBILE TARGET BASED ON COMMUNICATION

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IFAC Proceedings Volumes 2008年第2期41卷 10397-10402页

作者： Lei Liu Yongji Wang Dept. of Control Science and Engineering Huazhong Univ. of Sci. and Tech. Wuhan Hubei China 430074 Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan Hubei China 430074

Multi-robot tracking of mobile target is studied in the paper, which is based on the communication and sensors. For an independent tracking robot, the processes are separated into three layers and four tasks, and allocated to different robots for distinct roles in tracking, which is named the Distributed Decision control System (DDCS). After that, two tracking models, centralized and distributed models, are designed for multi-robot tracking. Furthermore, a Proportional Navigation Guidance Law (PNGL) and l-ϕ formation control algorithm are mentioned to realize the robot motion control. At last the simulation has shown the feasibility and validity of both models.

关键词： Multi-robot tracking DDCS PNGL Communication based l-ϕ formation control algorithm

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Improved Clonal Selection Algorithm based on Lamarckian Local Search Technique

Improved Clonal Selection Algorithm based on Lamarckian Loca...

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Congress on Evolutionary Computation

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

In this paper, we introduce Lamarckian learning theory into the clonal selection algorithm and propose a sort of Lamarckian clonal selection algorithm, termed as LCSA. The major aim is to utilize effectively the information of each individual to reinforce the exploitation with the help of Lamarckian local search. Recombination operator and tournament selection operator are incorporated into LCSA to further enhance the ability of global exploration. We compared LCSA with the clonal selection algorithm (CSA) in solving twenty benchmark problems to test the performance of LCSA. The results demonstrate that LCSA is effective and efficient in solving numerical optimization problems.

关键词： Artificial neural networks Immune system Cloning Optimization Evolutionary computation Benchmark testing Interpolation

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Unsupervised texture image segmentation using multiobjective evolutionary clustering ensemble algorithm

Unsupervised texture image segmentation using multiobjective...

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Congress on Evolutionary Computation

作者： Xiaoxue Qian Xiangrong Zhang Licheng Jiao Wenping Ma Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligence Information Processing Xidian University Xi'an China

Multiobjective evolutionary clustering approach has been successfully utilized in data clustering. In this paper, we propose a novel unsupervised machine learning algorithm namely multiobjective evolutionary clustering ensemble algorithm (MECEA) to perform the texture image segmentation. MECEA comprises two main phases. In the first phase, MECEA uses a multiobjective evolutionary clustering algorithm to optimize two complementary clustering objectives: one based on compactness in the same cluster, and the other based on connectedness of different clusters. The output of the first phase is a set of Pareto solutions, which correspond to different tradeoffs between two clustering objectives, and different numbers of clusters. In the second phase, we make use of the meta-clustering algorithm (MCLA) to combine all the Pareto solutions to get the final segmentation. The segmentation results are evaluated by comparing with three known algorithms: K-means, fuzzy K-means (FCM), and evolutionary clustering algorithm (ECA). It is shown that MECEA is an adaptive clustering algorithm, which outperforms the three algorithms in the experiments we carried out.

关键词： Evolutionary computation

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Needle segmentation using 3D quick randomized hough transform

Needle segmentation using 3D quick randomized hough transfor...

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1st International Conference on intelligent Networks and intelligent Systems, ICINIS 2008

作者： Qiu, Wu Ding, Mingyue Yuchi, Ming Institute for Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China Department of Biomedical Engineering School of Life Science and Technology Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)9780769533919

A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includes the 3D Quick Randomized Hough Transform (3DGHT), which is based on the 3D Randomized Hough Transform and coarse-fine searching strategy. We tested it with water phantom. The results show that our algorithm works well in 3D US images with angular deviation less than 1 and position deviation less than 1mm, and the computational time of segmentation with 35MB data is within 1s. © 2008 IEEE.

关键词： Hough transforms

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Lifting-Based Directionlet Transform for image Coding

Lifting-Based Directionlet Transform for Image Coding

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9th International Conference on Signal processing(第九届国际信号处理学术会议)(ICSP'08)

作者： Jing Bai Jiaji Wu Shan Lu Licheng Jiao Key laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information ProcessingXidian UniversityXi' an 710071P.R.China

In this paper,a new lifting scheme of directionlet transform(LDT) is presented,the corresponding multidirectional and anisotropic transform has latticebased separable filtering and subsampling along any two directions with rational *** design an adaptive compression algorithm based on LDT,using the quad-tree segmentation resulting optimized *** results show that our proposed compression algorithm for image coding outperforms the standard wavelet-based SPIHT and JPEG2000 both in terms of PSNR and visual quality,especially at the low-rate.

关键词： image coding Wavelet transforms Anisotropic magnetoresistance Compression algorithms Filtering Energy resolution Algorithm design and analysis image segmentation Transform coding Quantization

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A no-reference ringing metrics for images deconvolution

A no-reference ringing metrics for images deconvolution

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Bo-Xin Zuo Jin-Wen Tian De-Lie Ming State Key Laboratory of Education Commission for Image Processing and Intelligent Control Institute For Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

In this paper, we presented a ringing metric to evaluate the quality of images restored using iterative image restoration algorithms. A ringing metrics is used to assessment the restored images based on the Gabor filter. The experimental results validate the proposed method perform well over a wide range of restoration image ringing levels assessment. And the proposed model has given good agreement with observer ratings obtained in subjective experiments.

关键词： image restoration Gabor filters image edge detection Oscillators Deconvolution Maximum likelihood detection Band pass filters

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The Application of A Novel Target Region Extraction Model Based on Object-Accumulated Visual Attention Mechanism

The Application of A Novel Target Region Extraction Model Ba...

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International Conference on Natural Computation (ICNC)

作者： Jie Xiao Chao Cai Mingyue Ding Chengping Zhou Institute of Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

Combining bottom-up and top-down attention influences, a novel region extraction model which based on object-accumulated visual attention mechanism is proposed in this paper. Compared with early research, the new approach brings in prior information at the proper time, updates scan path dynamically, needs less computational resources and reduces the probability to direct the attention to a less-meaning area. The application to search an airport target in remote sensing image was provided, through which the novel mechanism that how visual attention chose the area was described. Compared with another two region extraction models, experimental results confirm the effectiveness of the approach proposed in this paper.

关键词： Data mining Object detection Computer applications Chaos Pattern recognition Artificial intelligence Laboratories image processing intelligent control Airports

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Dim small targets fusion detection in infrared image

Dim small targets fusion detection in infrared image

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yu-Qiu Sun Yu Zheng Jin-Wen Tian Jian Liu School of Information and Mathematics Yangtze University Jingzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery of Huazhong University of Science and Technology Wuhan China

To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave and long-wave infrared images and detect targets. Firstly, the source images are decomposed by wavelet transformation. In usual, targets in infrared images are man-made, and their fractal dimension is different comparing with natural background. In wavelet transformation domain high-frequency part, we calculate local fractal dimension and set up fusion rule to merge corresponding sub-images of two matching source images. In low-frequency, we extract local maximum gray level to fuse them. Then reconstruct image by wavelet inverse transformation and obtain fused result image. In fusion results, the contrast between targets and background has obvious changes. And targets can be detected using contrast threshold. The experimental results show that the method proposed in this paper using wavelet transformation fractal dimension to fuse dual band infrared images, and then detect targets is better than using mid-wave or long -wave infrared images detect targets alone.

关键词： Fractals Wavelet transforms Pixel Object detection Fuses Approximation methods Manganese

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Temporal pattern recognition using spiking neural networks for cortical neuronal spike train decoding

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IFAC Proceedings Volumes 2008年第2期41卷 5203-5208页

作者： Huijuan Fang Yongji Wang Jiping He Shan Liu Key Laboratory for Image Processing and Intelligent Control of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China (Tel: 86-27-87557284 The Harrington Department of Bioengineering and the Center for Neural Interface Design of The Biodesign Institute Arizona State University Tempe AZ 85287 USA

Most experimental and decoding algorithm studies of brain neural signals assume that neurons transmit information as a rate coding, but recent studies on the fast cortical computations indicate that temporal coding is probably a more biologically plausible scheme used by neurons. We introduce spiking neural networks (SNN) which consist of spiking neurons propagate information by the timing of spikes to analyze the cortical neural spike trains directly without temporal information lost. The SNN based temporal pattern classification is compared with the conventional artificial neural networks (ANN) based firing rate analysis. The results show that the SNN algorithm can achieve higher accuracy, which demonstrates that temporal coding is a viable code for fast neural information processing and the SNN approach is suitable for recognizing the temporal pattern in the cortical neural signals.

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