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International Conference on Computer Engineering and Technology, ICCET

作者： Jianwei Liang Haifeng You Xufa Wang Department of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei China

This article has been retracted by the publisher.

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Urban road network extraction from SAR image

Urban road network extraction from SAR image

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MIPPR 2007: Remote Sensing and GIS Data Processing and Applications;and Innovative Multispectral Technology and Applications

作者： Cheng, Pengxue Hu, Maolin Lab. of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469540

In this paper, a technique for the extraction of roads in a high resolution synthetic aperture radar (SAR) image is presented. And a three-step method is developed for the extraction of road network from space borne SAR image: the process of the feature points, road candidate detection and connection. Roads in a high resolution SAR image can be modeled as a homogeneous dark area bounded by two parallel boundaries. Dark areas, which represent the candidate positions for roads, are extracted from the image by a Gaussian probability iteration segmentation. Possible road candidates are further processed using the morphological operators. And the roads are accurately detected by Hough Transform, and the extraction of lines is achieved by searching the peak values in Hough Space. In this process, to detect roads more accurately, post-processing, including noisy dark regions removal and false roads removal is performed. At last, Road candidate connection is carried out hierarchically according to road established models. Finally, the main road network is established from the SAR image successfully. As an example, using the ERS-2SAR image data, automatic detection of main road network in Shanghai Pudong area is presented.

关键词： Feature extraction

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Inter-piconet interference mitigation schemes for converged BTLE and cellular network

Inter-piconet interference mitigation schemes for converged ...

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2011 International Conference on Wireless communications and Signal Processing, WCSP 2011

作者： Hu, Ying Wang, Guizhu Shan, Lianhai Yuan, Zhi Ouyang, Yuling Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China Shanghai Research Center for Wireless Communications Key Lab of Wireless Sensor Network and Communication CAS Shanghai China

ISBN: (纸本)9781457710100

In a Bluetooth Low Energy (BTLE) piconet, the master node controls the channel access by a simple polling scheme. Due to an absence of coordination among independent master nodes while accessing the wireless medium, devices will encounter high packet interference if many piconets are simultaneously operating in the same area. In this paper, we propose two schemes in the converged BTLE and cellular network, one is based on bad channel prediction for the BTLE piconets, and the other is based on frequency hopping sequences transformation. We compare the performance of the proposed algorithms with original scheme in the form of channel collision probability and new signaling overhead. The simulation results show that the proposed schemes can reduce channel collision probability significantly and simultaneously the new signaling overhead introduced to the downlink is not large. © 2011 IEEE.

关键词： Bluetooth

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Point matching of two images under large different resolution

Point matching of two images under large different resolutio...

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

作者： Ruan, Lei Hu, Maolin Lab. of Intelligent Computing and Signal Processing AnHui University Hefei AnHui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469502

Image matching is the first step in almost any 3D computer vision task, and hence has received extensive attention. In this paper, the problem is addressed from a novel perspective, which is different from the classic stereo matching paradigm. Two images with different resolutions, that is high resolution versus low resolution are matched. Since the high resolution image only corresponds to a small region of the low resolution one, the matching task therefore consists in finding a small region in the low resolution image that can be assigned to the whole high resolution image under the plane similarity transformation, which can be defined by the local area correlation coefficient to match the interest points and rectified by similarity transform. Experiment shows that our matching algorithm can be used for scale changing up to a factor of 6. And it is successful to deal with the point matching between two images under large scale.

关键词： Image matching

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Improved Lossless Data Hiding for JPEG Images Based on Histogram Modification

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Computers, Materials & Continua 2018年第6期55卷 495-507页

作者： Yang Du Zhaoxia Yin Xinpeng Zhang Key Laboratory of Intelligent Computing&Signal Processing Ministry of EducationAnhui UniversityHefei230601P.R.China Department of Computer Science Purdue UniversityWest lafayette47906USA School of Communication and Information Engineering Shanghai UniversityShanghai 200072P.R.China

This paper proposes a lossless and high payload data hiding scheme for JPEG images by histogram *** most in JPEG bitstream consists of a sequence of VLCs(variable length codes)and the appended *** VLC has a corresponding RLV(run/length value)to record the AC/DC *** achieve lossless data hiding with high payload,we shift the histogram of VLCs and modify the DHT segment to embed *** we sort the histogram of VLCs in descending order,the filesize expansion is *** paper’s key contribution includes:Lossless data hiding,less filesize expansion in identical pay-load and higher embedding efficiency.

关键词： Lossless data hiding histogram VLC JPEG.

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Energy Consumption and Time Delay optimization of MEC Based on MultiDimensional Game 5

Energy Consumption and Time Delay optimization of MEC Based ...

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5th IEEE International Conference on Cloud computing and Big Data Analytics, ICCCBDA 2020

作者： Wang, Hui Wang, Yi Lu, Xingjun Hu, Yanjun Anhui University Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Hefei230601 China Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China

ISBN: (纸本)9781728160245

Mobile edge computing (MEC) reduces latency and power consumption of mobile devices by deploying servers on the network edge. Due to the limited computing resources of the MEC server, excessive offloading of the users in local cells will bring unexpected queuing delay and high energy consumption. To deal with these problems, this paper proposes a Multi-user Queue Offloading multi-dimensional game algorithm (MQO). By the algorithm, users could choose the most suitable strategy, in which the strategy space is two-dimensional to satisfy different needs of different users to a certain extent, including the offload strategy and power control of users. Simulation results show that MQO can improve the performance of both overhead and offloading number with the increase of users. © 2020 IEEE.

关键词： Energy utilization

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Theoretical and empirical analyses of Evolutionary Negative Selection Algorithms for a combinational optimization problem

Theoretical and empirical analyses of Evolutionary Negative ...

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Xingxin Pei Wenjian Luo Nature Inspired Computation and Application Laboratory School of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China

Evolutionary Negative Selection Algorithms (ENSAs) could be regarded as hybrid algorithms of Evolutionary Algorithms (EAs) and Negative Selection Algorithms (NSAs). The average time complexity of ENSAs on combinational optimization problems has never been studied before. In this paper, the average time complexity of ENSAs on one combinational optimization problem is analyzed. The theoretical results demonstrate that, for the Two Max function, the ENSA with an appropriate matching threshold could perform better than the traditional (N+N) EA. Some simulation experiments on the combinational problem are also done, and the experimental results are consistent with theoretical results.

关键词： Algorithm design and analysis software algorithms Immune system Convergence Laboratories Computer applications Application software Computer science Evolutionary computation Biology computing

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A Clustering System for Gene Expression Data Based upon Genetic Programming and the HS-Model

A Clustering System for Gene Expression Data Based upon Gene...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Guiquan Liu Xiufang Jiang Lingyun Wen Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Cluster analysis is a major method to study gene function and gene regulation information for there is a lack of prior knowledge for gene data. Many clustering methods existed at present usually need manual operations or predetermined parameters, which are difficult for gene data. Besides, gene data possess their own characteristics, such as large scale, high-dimension, and noise. Therefore, a systematic clustering algorithm should be proposed to effectively deal with gene data. In this paper, a novel genetic programming (GP) clustering system for gene data based on hierarchical statistical model (HS-model) is proposed. And an appropriate fitness function is also proposed in this system. This clustering system can largely eliminate the infection of data scale and dimension. The proposed GP clustering system is applied to cluster the whole intact yeast gene data without dimensionality reduction. The experimental results indicate that the algorithm is highly efficient and can effectively deal with missing values in gene dataset

关键词： genetic programming cluster analysis missing value fitness function

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Extracting Qualitative States from Nonlinear Time Series Using Integration of Fuzzy c-Means and Hierarchical Clustering

Extracting Qualitative States from Nonlinear Time Series Usi...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Chenxi Shao Jinfeng Fan Xiaoping Chen Department of Computer Science and Technology University of Science and Technology of China Hefei Anhui China Anhui Province Key Laboratory of Software in Computing and Communication Hefei Anhui China

A novel method combined fuzzy c-means (FCM) and hierarchical agglomerative clustering (HAC) is presented to extract the qualitative states from reconstructed phase space by considering the dynamical relations of underlying nonlinear system. The qualitative state, in which all points have similar properties, is characterized by three measures, linear density, temporal reachability, and stable degree, which are defined as the criteria of merging subclasses. The time series sampled from a classic nonlinear system, Lorenz system, and electroencephalogram (EEG) signals are used to test this method. The results show that the qualitative states can be efficiently distinguished from these time series by the proposed method.

关键词： Space technology Nonlinear systems Clustering methods Fuzzy systems Merging Electroencephalography Chaotic communication Delay Computer science Laboratories

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Many-Modal Optimization by Difficulty-Based Cooperative Co-evolution

Many-Modal Optimization by Difficulty-Based Cooperative Co-e...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Wenjian Luo Yingying Qiao Xin Lin Peilan Xu Mike Preuss Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

Evolutionary multimodal optimization has received considerable attention in the past decade. Most existing evolutionary multimodal optimization algorithms are designed to solve problems with relatively few global optima. However, in real-world applications, the problems can possess a lot of global optima (and sometimes acceptable local optima). Finding more global optima can help us learn more about their landscapes and distributions. However, solving these problems with limited computational resources is a challenge for current algorithms. In this paper, many-modal optimization problems are studied, and each of them has more than 100 global optima. We first present a benchmark with 10 many-modal problems based on the existing multimodal optimization benchmarks. The numbers of global optima of these 10 problems vary from 108 to 7776. Second, we propose the difficulty-based cooperative co-evolution (DBCC) strategy for solving many-modal optimization problems. DBCC comprises four primary steps: problem separation, resource allocation, optimization, and solution reconstruction. The clonal selection algorithm is selected as the optimizer in DBCC. Experimental results demonstrate that DBCC provides satisfactory performance.

关键词： Optimization Benchmark testing Sociology Statistics Heuristic algorithms Resource management Search problems

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