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12th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2020

作者： Zhan-Jiang, Ji Wei, Shi School of Information and Electronic Engineering Wuzhou University China Guangxi Colleges and Universities Key Lab. of Image Processing and Intelligent Information System Wuzhou University China Guangxi Colleges and Universities Key Laboratory of Professional Software Technology Wuzhou University China Party Committee Office Wuzhou Vocational College China

ISBN: (纸本)9781728170817

The expansion property and chain mixing property have an important significance in terms of theory and application. The concept of the expansion property and chain mixing property are introduced in this paper. We study their dynamical properties. The following result are obtained: (1)Letbe the hyperspace of. Ifis expansive, thenis expansive;(2)Letbe the hyperspace of. Ifis chain mixing, thenis chain mixing;(3)Letbe the hyperspace of. Ifis chain transitive, thenis chain transitive;These results enriched the theory of the expansion property and chain mixing property of topological group. © 2020 IEEE.

关键词： Topology

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The research of G-chain transitive and G-chain mixing on the hyperspace of topological group action 12

The research of G-chain transitive and G-chain mixing on the...

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12th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2020

ISBN: (纸本)9781728170817

G-chain transitive and G-chain mixing have an important significance in terms of theory and application. According to the definition of chain transitive and chain mixing, we give the concept of G-chain transitiveand G-chain mixing in this paper. By inference, some conclusions of the hyperspace were extended to the hyperspace of topological group action. We have the following result: (1)Letbe the hyperspace of. Ifis a G-chain transitive map, thenis a G-chain transitive map;(2)Letbe the hyperspace of. Ifis a G-chain mixing map, thenis a G-chain mixing map;(3)Letbe the hyperspace ofandbe a equivariant map. All non-empty open set are invariable for. Thenis a G-exact map if and only ifis a G-exact map. These results enriched the theory of the G-chain transitive and G-chain mixing on the hyperspace of topological group action. © 2020 IEEE.

关键词： Group theory

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DIRECTIONAL CLASSIFICATION OF CORTICAL SIGNALS USING A LIQUID STATE MACHINE

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IFAC Proceedings Volumes 2008年第2期41卷 9596-9600页

作者： Jiangshuai Huang Huijuan Fang Yongji Wang Key Lab. for Image Processing & Intelligent Control of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Liquid State Machine (LSM) is a newly developed computational model with many interesting properties. It has great advantages of dealing with biologic computing when compared to the traditional computational model. In this paper, the LSM was used to deal with the direction classification problem of the spike series which were distilled from the neurons in motor cortex of a monkey. In the output layer, a linear regression and back-propagation are employed as the training algorithms. Compare to outcomes of the two algorithms, it is showed that ideal classification results were derived when using BP as the training algorithm.

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Color image filtering based on impulsive noise detection

Color image filtering based on impulsive noise detection

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MIPPR 2007: Automatic Target Recognition and image Analysis;and Multispectral image Acquisition

作者： Li, Dehua Jin, Lianghai Yao, Xingzhong Xiong, Caiquan State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Second Artillery Command College Wuhan 430012 China School of Computer Science Hubei University of Technology Wuhan 430068 China

ISBN: (纸本)9780819469502

This paper introduces a new class of switching vector median filter. The proposed algorithm first uses four directional masks to analyze the color difference between the central pixel and its neighborhood pixels in the RGB color space and classify each color pixel into noisy pixel or noise-free one, and then employs the standard vector median filtering operations in the detected noisy locations to restore the corrupted pixels and leave the noise-free ones unchanged. The simulation results show that the proposed method excellently suppresses impulsive noise as well as preserving the image details well, and significantly outperforms the existing vector filtering solutions in terms of both the objective measures and the perceptual visual quality.

关键词： Color image processing

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Multiobjective social evolutionary algorithm based on multi-agent

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Ruan Jian Xue Bao/Journal of Software 2009年第7期20卷 1703-1713页

作者： Pan, Xiao-Ying Liu, Fang Jiao, Li-Cheng Key Lab. of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China School of Computer Science and Engineering Xidian University Xi'an 710071 China

In this paper, a multi-agent social evolutionary algorithm is proposed for multiobjective optimization problems. It completes the search process by the agent evolution. MOMASEA (multi-agent social evolutionary algorithm for multiobjective) defines the trust degree to denote the historical information of agents, and the neighborhood of agent is confirmed by it. According to the characteristic of multiobjective problems, three evolutionary operators are designed to complete the whole evolutionary process. The experimental results show that MOMASEA has a good convergence to the Pareto set. Furthermore, the analysis of the mode for instructs local environment verified that importing acquaintance net model can speed up the convergence effectively. © by Institute of Software, the Chinese Academy of Sciences.

关键词： Multiobjective optimization

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Electroencephalogram Signal Analysis Based on the Improved k-nearest Neighbor Network

Electroencephalogram Signal Analysis Based on the Improved k...

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International Congress on image and Signal processing, BioMedical Engineering and Informatics

作者： Xian Yu Chengcheng Liu Jun Wang Jiafei Dai Jin Li Fengzhen Hou Image Processing and Image Communications Key Lab Nanjing University of Posts and Telecommunications Nanjing General Hospital of Nanjing Military Command College of Physics and Information Technology Shaanxi Normal University School of Science China Pharmaceutical University

ISBN: (纸本)9781509037117

In this paper, we propose a method to analyze epileptic electroencephalogram based on time series that is transformed from improved k-nearest neighbor network. The study of complex networks has become a hot research of electroencephalogram signal. Electroencephalogram time series generated by the network keeps node information of network, so researching the time series from the network can also achieve the purpose of studying epileptic electroencephalogram. The results of this experiment show that studying power spectrum of time series from the network is more easily than the power spectrum of time series directly generated from brain data to distinguish between normal and epileptic patients. In addition, studying the clustering coefficient of improved k-nearest neighbor network is also able to distinguish between normal and patients with epilepsy. This study can provide an important reference for the study of epilepsy and clinical diagnosis.

关键词： analysis of electroencephalogram signals improved k-nearest neighbor network time series epilepsy

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Anchored Neighborhoods Search Based on Global Dictionary Atoms for Face Photo-Sketch Synthesis

Anchored Neighborhoods Search Based on Global Dictionary Ato...

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2019第十一届数字图像处理国际会议

作者： Feng Liu Ran Xu Jieying Zheng Qiuli Lin Zongliang Gan College of Educational Science and Technology Nanjing University of Posts and Telecommunications Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications

Example-based face sketch synthesis technology generally requires face photo-sketch images with face alignment and size *** break through the limitation,we propose a global face sketch synthesis method:In training,all training photo-sketch patch pairs are collected together and a photo feature dictionary is learned from the photo *** each atom of the dictionary,its K closest photo-sketch patch pairs are clustered,namely "Anchored Neighborhood".In testing,for each test photo patch,we search its nearest photo patch in the Anchored Neighborhood determined by its closest atom,then the corresponding sketch patch is the *** the same way,we train and test in the high-frequency domain and synthesis the high-frequency ***,the fusion of the initial and the high-frequency results is the final *** experiments on three public face sketch datasets and various real-world photos demonstrate the effectiveness and robustness of the proposed method.

关键词： Face sketch synthesis Dictionary learning Dictionary atom Anchored neighborhood image patch

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Vehicle Color Recognition Based on Superpixel Features

Vehicle Color Recognition Based on Superpixel Features

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2019第十一届数字图像处理国际会议

作者： Qiuli Lin Feng Liu Qiang Zhao Ran Xu Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications College of Educational Science and Technology Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications

In this paper,a novel methodology is presented to settle the region of interest(ROI) detection problem in vehicle color recognition so as to remove the redundant components of vehicles that interfere greatly with color *** order to make full use of the local color and spatial information,vehicle images are divided into different superpixels at *** spatial relationship between superpixels and the outermost pixels is then used for the background removal of vehicle *** comparing with the vehicle window clustering centroids obtained by k-means,the superpixels close to the universal color characteristics of windows are removed so that the dominant color superpixels are ***,a linear Support Vector Machine classifier is trained for color *** experiments demonstrate that the proposed methodology is effective for color region of interest detection and thus contribute to vehicle color recognition.

关键词： vehicle color recognition region of interest superpixel universal color characteristics Support Vector Machine

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Effective Scheme for Global Abnormal Event Detection for Surveillance Video

Effective Scheme for Global Abnormal Event Detection for Sur...

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2016 International Conference on communications, Information Management and Network Security (CIMNS2016)

作者： Fangxu Dong Dong Hu Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781510830981

An effective algorithm for global abnormal detection from surveillance video is proposed in this paper. The algorithm is based on sparse representation. To deal with the illumination change in video scenes, specific feature extract methods are designed for corresponding illumination conditions. In the case of non-uniform illumination, features are extracted directly on the original image;in the case of uniform illumination, features are extracted on the binary image obtained by threshold segmentation on the difference image, where the thresholds are computed by the Otsu's method. The features extracted on normal video are used to learn an over-complete dictionary. Then, the sparse reconstruction cost over the dictionary is used to detect abnormal events. Experiments on the open global abnormal dataset and the comparison to the state-of-the-art methods validate effectiveness and quickness of our algorithm.

关键词： abnormal detection illumination change binary images sparse reconstruction cost

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A novel path planning method based on path network

A novel path planning method based on path network

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Li, Shidong Ding, Mingyue Cai, Chao Institute for Pattern Recognition and Artificial Intelligence National Lab. for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China Hubei University for Nationalities Enshi Hubei 445000 China College of Life Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Traditional path planning methods are too slow to meet the real-time requirement in practical applications. In order to solve this problem, an idea of path net was proposed in this paper. The path planning procedure is divided into two steps: network segment planning and segment assembling. The first step was done with Fast Marching Method, including port selection of segment and network segment planning. Second step, the A* searching method was chosen to select segments for assembling. Experiments demonstrated that our method can obtain an optimal route in a few of seconds after the start and goal are given while several minutes are needed for traditional methods. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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