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检索条件"机构=Image Processing Department Computer Software Technology Laboratory"

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Zhang, Zhujin Wang, Shuo Zhang, Xingyi Zhang, Zheng Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Computer and Information Science University of South Australia Adelaide SA 5095 Australia Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9781424464388

Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with time complexity O(n2), and find another important advantage in the representation: no degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the representation. The approach adopts four elements of covariance matrix as a descriptor, and is illustrated on the first exon of beta-globin genes from 11 different species. © 2010 IEEE.

关键词： DNA sequences

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Algorithm for elliptic curve diffie-hellman key exchange based on DNA tile self-assembly

Algorithm for elliptic curve diffie-hellman key exchange bas...

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作者： Cheng, Zhen Huang, Yufang Chen, Zhihua Shi, Xiaolong Xu, Jin Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology 430074 Wuhan China School of Electronics Engineering and Computer Science Peking University 100871 Beijing China

DNA tile self-assembly is a promising paradigm for nanotechnology. Recently, many researches show that computation by DNA tile self-assembly maybe scalable. In this paper, we propose the algorithm for elliptic curve Diffie-Hellman key exchange based on DNA tile self-assembly. First we give the DNA tile self-assembly model to compute the scalar multiplication, then we can successfully implement the Diffie-Hellman key exchange over elliptic curve by extracting the result strand of the scalar multiplication. Copyright © 2010 American Scientific Publishers. All rights reserved.

关键词： Self assembly

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Algorithmic tile assembly for solution of the maximum clique problem

Algorithmic tile assembly for solution of the maximum clique...

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作者： Huang, Yufang Xu, Jin Cheng, Zhen Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

The maximum clique problem has diverse applications in the field of pattern recognition, computer vision, information processing etc. The connection between self-assembly and computation has implied that the tile assembly can perform arithmetical computation. Approaches to algorithmic self- assembly require the use of DNA nanostructures, called tiles, which have efficient computational power, and convenient input and output mechanisms. We present a theoretical tile assembly model for the maximum clique problem. We take some transformation to the maximum clique problem and convert it into the 0-1 programming problem. By use of the huge parallelism inherent in the arithmetic tile assembly, it outputs a reporter strand which includes the solution to the problem. It is proved that this method can be extended to the maximum independent set problem and 0-1 programming problem. The arithmetic tile assembly model proposed here can give the answer by use of 0(2n2 + 2mn+ 12n) tile types in time linear with the input size. Copyright © 2010 American Scientific Publishers. All right resered.

关键词： Computational complexity

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Spectral representation of DNA sequences and its application

Spectral representation of DNA sequences and its application

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Zhang, Zhujin Liu, Lin Li, Jiuyong Zhang, Zheng Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Computer and Information Science University of South Australia Adelaide SA 5095 Australia

ISBN: (纸本)9781424464388

Randí;et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation and prove that the claim is correct, and that it also avoids degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the spectral representation. The method adopts M value to characterize a graphical representation and uses 24-component vector as descriptor. The approach is illustrated on the complete coding sequence of beta-globin genes from 7 different species. © 2010 IEEE.

关键词： DNA sequences

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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International Conference on Mechatronics and Automation

作者： Wang, Yuanyu Li, Yuanzong Zhang, Tianxu Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan CO 030024 China College of Mechanical Engineering TaiYuan University of Technology TaiYuan CO 030024 China Institute for Pattern Recognition and A.I. State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology WuHan CO 430074 China

ISBN: (纸本)9781424451418

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments. © 2010 IEEE.

关键词： Dust

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

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International Conference on Intelligent and Advanced Systems, ICIAS

作者： Mahdi Ramezani Amin Heidari Emad Fatemizadeh Hamid Soltanian-Zadeh Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearest-neighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Clustering algorithms Algorithm design and analysis Correlation Approximation methods Independent component analysis Time series analysis Approximation algorithms

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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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Matrix representation of spiking neural P systems

Matrix representation of spiking neural P systems

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11th International Conference on Membrane Computing, CMC 2010

作者： Zeng, Xiangxiang Adorna, Henry Martínez-Del-Amor, Miguel Ángel Pan, Linqiang Pérez-Jiménez, Mario J. Image Processing and Intelligent Control Key Laboratory of Education Ministry Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China University of the Philippines Diliman 1101 Quezon City Philippines Research Group on Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Avda. Reina Mercedes s/n 41012 Sevilla Spain

ISBN: (纸本)3642181228

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this work, a discrete structure representation of SN P systems with extended rules and without delay is proposed. Specifically, matrices are used to represent SN P systems. In order to represent the computations of SN P systems by matrices, configuration vectors are defined to monitor the number of spikes in each neuron at any given configuration;transition net gain vectors are also introduced to quantify the total amount of spikes consumed and produced after the chosen rules are applied. Nondeterminism of the systems is assured by a set of spiking transition vectors that could be used at any given time during the computation. With such matrix representation, it is quite convenient to determine the next configuration from a given configuration, since it involves only multiplication and addition of matrices after deciding the spiking transition vector. © 2010 Springer-Verlag.

关键词： Vectors

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Hessian based image structure adaptive gradient vector flow for parametric active contours

Hessian based image structure adaptive gradient vector flow ...

引用

IEEE International Conference on image processing

作者： Y.Q. Wang W.F. Chen T.L. Yu Y.T. Zhang Tianjin Key Laboratory of Intelligent Computing & Novel Software Technology Tianjin University of Technology Tianjin China Key Laboratory of Image Processing Southern Medical University Guangzhou China Department of Radiology General Hospital Tianjin Medical University Tianjin China

Active contours have been one of the most successful methods for image segmentation during the last two decades, but one of the shortcomings of being unable to converge to concavity is a handicap to its effectiveness. In order to address this issue, the gradient vector flow (GVF) was put forth. Although there have been a great number of works on GVF, the image structure has seldom been incorporated into GVF algorithm. In this work, the image structure characterized by the Hessian matrix is incorporated into the GVF algorithm by reformulating the smoothness constraint of GVF into matrix form. In this way, the associated diffusion PDEs are anisotropic and the modified GVF snake can converge to very long concavity and preserve weak edge simultaneously. Experiments and comparisons are presented to demonstrate the properties of the proposed strategies.

关键词： Active contours image edge detection Force image segmentation Mathematical model Tensile stress Equations

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Volume-based magnetic resonance brain image classification

Volume-based magnetic resonance brain image classification

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International Conference on Genetic and Evolutionary Computing

作者： Chiou, Yaw-Jiunn Chai, Jyh-Wen Chen, Clayton Chi-Chang Chen, Shih-Yu Chen, Hsian-Min Ouyang, Yen-Chieh Su, Wu-Chung Tsai, Ching Tsorng Yang, Ching-Wen Lee, San-Kan Chang, Chein-I Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Section of Radiology College of Medicine China Medical University Taichung Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung Taiwan Department of Biomedical Engineering Hungkuang University Taichung Taiwan Computer Science Department Tunghai University Taichung Taiwan Computer Center Taichung Veterans General Hospital Taichung Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780769542812

This paper develops a volume-based technique, called Volume Sphering Analysis (VSA) which can process all acquired Magnetic Resonance (MR) image slices-formed image cube using only one set of training samples obtained from an image slice. So, several significant advantages and benefits can be gained from our proposed VSA. In the past, when MR image classification is performed, each image slice requires its own specific training samples and training samples obtained from one slice are not applied to another slice. The VSA allows users to reduce computational time. In addition, it saves significant effort in selecting training samples for each of image slices. Thirdly, it is robust to all image slices compared to the traditional one-slice MR image classification which is sensitive to each image slice. Experimental results demonstrate that the VSA performs as well as does that using specifically selected training samples for individual image slices. © 2010 IEEE.

关键词： Support vector machines

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