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Detecting flood change with multitemporal SAR images based on difference images fusion and fuzzy degree of nearness

Detecting flood change with multitemporal SAR images based o...

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Li, Jinji Jiao, Licheng Zhang, Xiangrrong Hou, Biao Yang, Dongdong Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

In this paper, we present a novel approach for detecting the changed regions caused by flooding events in multi-temporal SAR images. And the proposed method concludes two parts: 1) constructing difference image (DI) by fusion strategy proposed in this paper;2) producing change-detection map based on FCM and fuzzy degree of nearness. Experimental comparisons on real multi-temporal SAR images indicate that the proposed method can reduce the affection by speckle noise. Meanwhile, the proposed method can accurately detect the interested changed regions. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Synthetic aperture radar

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Gene transposon based clonal selection algorithm for clustering

Gene transposon based clonal selection algorithm for cluster...

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11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009

作者： Liu, Ruochen Sheng, Zhengchun Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781605583259

Inspired by the principle of gene transposon proposed by Barbara McClintock, a new immune computing algorithm for clustering multi-class data sets named as Gene Transposition based Clone Selection Algorithm (GTCSA) is proposed in this paper, The proposed algorithm does not require a prior knowledge of the numbers of clustering;an improved variant of the clonal selection algorithm has been used to determine the number of clusters as well as to refine the cluster center. a novel operator called antibody transposon is introduced to the framework of clonal selection algorithm which can realize to find the optimal number of cluster automatically. The proposed method has been extensively compared with Variable-string-length Genetic Algorithm(VGA)based clustering techniques over a test suit of several real life data sets and synthetic data sets. The results of experiments indicate the superiority of the GTCSA over VGA on stability and convergence rate, when clustering multi-class data sets. Copyright 2009 ACM.

关键词： Genes

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Synthetic aperture radar automatic target recognition based on curvelet transform

Synthetic aperture radar automatic target recognition based ...

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wang, Shuang Liu, Zhuo Jiao, Licheng He, Jun Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

A novel synthetic aperture radar (SAR) automatic target recognition (ATR) approach based on Curvelet Transform is proposed. However, the existing approaches can not extract the more effective feature. In this paper, our method is concentrated on a new effective representation of the moving and stationary target acquisition and recognition (MSTAR) database to obtain a more accurate target region and reduce feature dimension. Firstly, MSTAR database can be extracted feature through the optimal sparse representation by curvelets to obtain a clear target region. However, considering the loss of part of edges of image. We extract coarse feature, which is to compensate fine feature error brought by segmentation. The final features consisting of fine and coarse feature are classified by SVM with Gaussian radial basis function (RBF) kernel. The experiments show that our proposed algorithm can achieve a better correct classification rate. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Automatic target recognition

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Quantum-inspired evolutionary clustering algorithm based on manifold distance 09

Quantum-inspired evolutionary clustering algorithm based on ...

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2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09

作者： Yangyang, Li Hongzhu, Shi Maoguo, Gong Ronghua, Shang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781605583266

Based on the concepts and principles of quantum computing, a quantum-inspired evolutionary algorithm for data clustering (QECA) is proposed in this paper. And a novel distance measurement index called manifold distance is introduced. These attribute data are the main source of clustering problem, due to its complex distribution, most clustering algorithms available are only suitable for these types of characteristic data. In this study, a new algorithm which can deal with these data with manifold distribution is more effective. The main motives of using QECA consist in searching for appropriate cluster center so that a similarity metric of clusters are optimized more quickly and effectively. The superiority of QECA over fuzzy c-means (FCM) algorithm and immune evolutionary clustering algorithm (IECA) is extensively demonstrated in our experiments. Copyright 2009 ACM.

关键词： Clustering algorithms

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Algorithm of partition based network boosting for imbalanced data classification

Algorithm of partition based network boosting for imbalanced...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Shuiping, Gou Hui, Yang Licheng, Jiao Xiong, Zhuang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424469178

Network Boosting (NB) is an ensemble learning method which combines weak learners together based on a network and can learn the target hypothesis asymptotically. NB has higher generalization ability compared to Bagging and AdaBoost. But, when datasets are class-imbalanced, the performance of NB will decrease quickly. In order to solve this problem, we present a Partition based Network Boosting method (PNB) to classify imbalanced data. For PNB method, every classifier node of the classifier network is provided with the same number of training data which are all of same weights. The classifier in the network is built by the balanced training set sampled from the training data according to the weights record of the training data it holds. And then, the weights of the instances of every node classifier are updated based on the classification results of self-node and its neighbor nodes. The classifier network is trained repeatedly in such a way. Weight factor of hypothesis in the training progress is introduced to improve the performance. The final classification is formed by all the hypotheses of the classifier network learned during the training progress so that the label of new instances can be decided by the weight voting. The experimental results on UCI data and imbalanced biomedical data show that the PNB algorithm has better AUC and recall performance compared with NB learning machine. © 2010 IEEE.

关键词： Adaptive boosting

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control reconfiguration of new strap-on boosted launch vehicle [PRC] with deadlocked swing Engines

Control reconfiguration of new strap-on boosted launch vehic...

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作者： Liu, Lei Yin, Biao Wang, Yongji Deng, Zhixiang Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780955529337

To enhance the reliability of launch vehicle attitude control systems and prevent the control invalidation caused by swing engine deadlock, a control reconfiguration of fault-tolerant control is proposed. Firstly, the coupling identity between the channels is discussed based on the dynamic model of the vehicle. Then, under the assumption of no rolling motion, we study the swing angles reconfiguration method based on the moment balance principle, and then deduce the relationship between the swing angle of the deadlocked engines and the engines still operate well. From the rationality analysis, the safe bound of the deadlocked engine and reconfiguration conditions are proposed under several assumptions. Finally, the numerical simulation of rocket attitude control based on the discussed reconfiguration strategy is given to demonstrate that the variance of the control affect by the deadlocked engine could be rectified by other booster-engines effectively.

关键词： Launch vehicles

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SAR target recognition based on improved sparse LSSVM

SAR target recognition based on improved sparse LSSVM

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhang, Xiangrong Zhang, Yifan Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

An Improved Fast Sparse Least Squares Support Vector Machine (IFSLSSVM) is proposed for Synthetic Aperture Radar (SAR) target recognition. Least Squares Support Vector Machine (LSSVM) is a least square version of Support Vector Machine (SVM), but it lacks the sparseness compared with SVM. IFSLSSVM, which combines the incremental learning and decremental learning, selects those important samples as the support vectors, and implements pruning by a certain condition, can solve the non-sparse problem of LSSVM effectively. Benchmarking UCI datasets are firstly used for testing the performance of our algorithm, followed by SAR target recognition. Experimental results on MSTAR SAR dataset show that IFSLSSVM is an effective SAR target recognition approach (SAR-ATR), which not only reduces the number of support vectors but also enhances the recognition rate. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Support vector machines

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An overview of Hierarchical Temporal Memory: A new neocortex algorithm

An overview of Hierarchical Temporal Memory: A new neocortex...

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Chen, Xi Wang, Wei Li, Wei Institute of System Engineering Huazhong University of Science and Technology Education Ministry of China Wuhan Hubei 430074 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory Education Ministry of China China

ISBN: (纸本)9780956715715

The overview presents the development and application of Hierarchical Temporal Memory (HTM). HTM is a new machine learning method which was proposed by Jeff Hawkins in 2005. It is a biologically inspired cognitive method based on the principle of how human brain works. The method invites hierarchical structure and proposes a memory-prediction framework, thus making it able to predict what will happen in the near future. This overview mainly introduces the developing process of HTM, as well as its principle, characteristics, advantages and applications in vision, image processing and robots movement, some potential applications by using HTM, such as thinking process, are also put forward. © 2012 Huazhong Univ of Sci & Tec.

关键词： Forecasting

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An online ascent phase trajectory reconstruction algorithm using Gauss Pseudospectral Method

An online ascent phase trajectory reconstruction algorithm u...

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Zhang, Da Lu, Xuefang Liu, Lei Wang, Yong Ji Key Labo-ratory of Ministry of Education for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780956715715

In this paper, we present an online ascent phase trajectory reconstruction algorithm using Gauss Pseudospectral Method. Gauss Pseudospectral Method (GPM) was used to transform the ascent phase trajectory optimization problem into Nonlinear Program Problem (NLP), we solve the problem using a optimization software named GPOPS in matlab. Using this method we can calculate the optimal trajectory control volume and feedback to update the guidance commands online. Credible analysis of the optimized results has been done to prove its accuracy. At last, we compare the trajectory recon- struction algorithm to a law without reconstruction algorithm via simulation with aerodynamic and thrust disturbance. The simulation results indicate that the method proposed above offers improved performance and has ability for real-time calculating. © 2012 Huazhong Univ of Sci & Tec.

关键词： Nonlinear programming

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Information Extraction of Bionic Camera-Based Polarization Navigation Patterns Under Noisy Weather Conditions

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Journal of Shanghai Jiaotong university(Science) 2020年第1期25卷 18-26页

作者： AH SAN Muhammad CAI Yunze ZHANG Weidong Department of Automation Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaMinistry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Marine Intelligent Equipment and System Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China

Light polarization is the phenomenon that describes the oscillations and orientations of the light *** light is a source of substantial cue for navigation in many marine and land-dwelling *** work investigates the challenges of obtaining information regarding polarization under various conditions by observing the phenomenology of the ommatidium in many *** conditions can be because of haze or the presence of clouds in the *** molecules are greater in volume and scale in such atmospheric *** sunlight crosses through these molecules of aerosol,its polarization information is *** distorted pattern has a little or no information on neutral points of light *** the basis of the relationship bet ween wavelength of sunlight and polarization,we propose a novel hue based color mixing(HBCM)model to calculate the polarization information and orientation information more accurately and *** method improves the symmetries of polarization patterns and eliminates the effect of *** of polarization patterns are compared with red,green and blue(RGB)spectrum and these differences are quantified and compared especially under high noisy weather conditions.

关键词： light polarization ommatidium aerosols neutral points hue based color mixing(HBCM)

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