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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Liu, Fan Jiao, Licheng Yang, Shuyuan 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)9781424427314

A new method about SAR image despeckling is proposed in this paper, this method is achieved by combining wavelet kernel transform (WKT) and Gaussian Scale Mixture model (GSM). WKT is a multiscale transform which is based on machine learning model. By analysis the distribution of the coefficients after WKT, these coefficients are similar to Gaussian distribution, and these noised coefficients are distributed as Gaussian too, but are independence with non-noised coefficients. In this paper, we construct the neighbor model based on the coefficients after WKT, and use the Bayes least mean square to despeckle the spots in SAR images, and the model describes the edge distribution of coefficients. We use the proposed method to process the SAR images, and the results demonstrate that this method can obtain better denoising images than Lee filter, wavelet transform etc. ©2009 IEEE.

关键词： Synthetic aperture radar

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Semi-Supervised Classification of Data Streams by BIRCH Ensemble and Local Structure Mapping

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Journal of Computer Science & Technology 2020年第2期35卷 295-304页

作者： Yi-Min Wen Shuai Liu Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin 541004China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin 541004China

Many researchers have applied clustering to handle semi-supervised classification of data streams with concept ***,the generalization ability for each specific concept cannot be steadily improved,and the concept drift detection method without considering the local structural information of data cannot accurately detect concept *** paper proposes to solve these problems by BIRCH(Balanced Iterative Reducing and Clustering Using Hierarchies)ensemble and local structure *** local structure mapping strategy is utilized to compute local similarity around each sample and combined with semi-supervised Bayesian method to perform concept *** a recurrent concept is detected,a historical BIRCH ensemble classifier is selected to be incrementally updated;otherwise a new BIRCH ensemble classifier is constructed and added into the classifier *** extensive experiments on several synthetic and real datasets demonstrate the advantage of the proposed algorithm.

关键词： semi-supervised classification clustering data stream concept drift

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A method of threaten ordering based on cloud model theory

A method of threaten ordering based on cloud model theory

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

作者： Yu, Xin Wang, Hua 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

Situation assessment (SA) is a complex decision-making process in modern aerial defense system. Threaten ordering (TO) problem is one of the most difficult steps in SA. There are a lot of uncertain factors in TO, and traditional evaluation methods have some disadvantages on algorithm measures. To overcome these disadvantages, a method of TO based on cloud model theory is proposed. Firstly the factors of air-targets threat evaluation are analyzed in this paper. Then the reasoning mechanism base on cloud model is designed. In this step the cloud model is used to depict the attributes of target, the model parameters are defined, and the reasoning rule library is established by using the method of Multiple Attribute Decision Making (MADM). The data of targets were input to the reasoning mechanism, and the threat value was gained. Finally the simulation experiments are given to verify the validity of the method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Decision making

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A general end-to-end diagnosis framework for manufacturing systems

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National Science Review 2020年第2期7卷 418-429页

作者： Ye Yuan Guijun Ma Cheng Cheng Beitong Zhou Huan Zhao Hai-Tao Zhang Han Ding School of Artificial Intelligence and Automation MOE Key Lab of Intelligent Control and Image Processing Huazhong University of Science and Technology State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology

The manufacturing sector is envisioned to be heavily influenced by artificial-intelligence-based technologies with the extraordinary increases in computational power and data volumes. A central challenge in the manufacturing sector lies in the requirement of a general framework to ensure satisfied diagnosis and monitoring performances in different manufacturing applications. Here, we propose a general data-driven,end-to-end framework for the monitoring of manufacturing systems. This framework, derived from deep-learning techniques, evaluates fused sensory measurements to detect and even predict faults and wearing conditions. This work exploits the predictive power of deep learning to automatically extract hidden degradation features from noisy, time-course data. We have experimented the proposed framework on 10 representative data sets drawn from a wide variety of manufacturing applications. Results reveal that the framework performs well in examined benchmark applications and can be applied in diverse contexts,indicating its potential use as a critical cornerstone in smart manufacturing.

关键词： manufacturing systems deep learning diagnosis and monitoring

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An improved watershed-based SAR image segmentation algorithm

An improved watershed-based SAR image segmentation algorithm

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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 Zhang, Xiaojing Jiao, Licheng Zhang, Xiangrong 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

The watershed transform is a well-established tool for image segmentation. However, watershed segmentation is often not effective for Synthetic Aperture Radar (SAR) images which are generally corrupted by coherent speckle noise. This paper presents a novel approach for SAR image segmentation using watershed segmentation algorithm combined with Otsu. The aim of this study is to improve the generalization of watershed techniques and to construct a well segmentation of SAR images. Typically, Otsu is used to produce inner mark and external mark. Then we use the mark to modify the gradient image of the SAR image. Additionally, rather than flooding the gradient image, we use the gradient image modified by the mark as input to the watershed algorithm. Experimental results demonstrate the superior performance of the improved watershed-based SAR segmentation. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image segmentation

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The despeckling of SAR image based on the curvelet transform

The despeckling of SAR image based on the curvelet transform

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Hou, Biao Liu, Honghua 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)9781424427314

A novel method of speckle suppression for SAR image based on the curvelet transform is presented. A Bayesian shrinkage factor is derived to shrink the curvelet coefficients, then the mean filter and the nonlinear anisotropic diffusion are used to deal with the reconstructed image. Experimental results show that the proposed method can effectively suppress the speckle while keep the edge and other details. ©2009 IEEE.

关键词： Synthetic aperture radar

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An improved contour detection method based on level set and watershed transform

An improved contour detection method based on level set and ...

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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 Fu, Shenggao Jiao, Licheng Zhang, Xiaojing 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, an improved contour detection method based on level set and watershed transform is proposed. It is performed on coarse-to-fine approach: 1) primary contours detected by using level set evolution;2) accurate contours detected by watershed transform. The combined method utilizes the advantages of level set method and watershed transform. Experimental results show that our method could detect accurate contours and gain great improvement compared with level set evolution and watershed transform. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Numerical methods

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A method of COA based on multi-agent evolutionary algorithm

A method of COA based on multi-agent evolutionary algorithm

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

作者： Yu, Xin Wang, Hui 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

Planning detailed military course of action (COA) is very complex and time consuming. In this paper, a method based on multi-agent evolutionary algorithm was presented to solve COA' resource management and scheduling problems. Each individual can be seen as an agent, in order to realize the local perceptivity of agents, the environment is organized as a latticelike structure. Each agent is fixed on a lattice point and it can only interact with its *** agent behaviors which are competition behavior and self-learning behavior are designed. In this work, constraint functions are considered as functions to be optimized like the objectives and then added in competition strategy to deal with the multi-objective aspect of resource-constrained project scheduling problems. This approach avoids the use of a penalty function to deal with constraints. At the same time, the added constraint functions could make the whole algorithm evolving feasible. The simulation results demonstrated that this approach could improve searching ability of this algorithm, and the precision of this method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Evolutionary algorithms

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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...

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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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Improvement of Bandelets in cost function and coding strategy for SAR image compression

Improvement of Bandelets in cost function and coding strateg...

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Yang, Shuyuan Wu, Ruixia Meng, Huixiao 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)9781424427314

Synthetic aperture radar (SAR) data collections can cover large areas at high resolution, generating massive amounts of data. Many existed transform-based compression techniques can effectively reduce the costs of storage and transmission with slight loss of information. As a new developed multi-resolution geometry analysis tool, Bandelet can make full use of intrinsic geometry regularity of images and exhibit enormous potential in image compression. In this paper, we propose a low complexity Bandelet transform for SAR image compression. A new cost function is defined to determine the optimal geometric flows in each dyadic squared sub-block of images, and an optimization of low frequency component followed by EBCOT coding of the Bandelet coefficients are employed. Some experiments are taken on some Ku-band SAR images came from Sandia National Laboratories and the results show the superiority of our proposed method over JPEG2000 and the second generation Bandelet in PSNR, ENL and EPI. ©2009 IEEE.

关键词： Cost functions

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