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Optical focusing feature of single element in 128×128 elements electrically controllable cylindrical liquid crystal lens array

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Chinese Optics Letters 2010年第3期8卷 329-331页

作者：李晖刘侃张新宇张天序沈绪榜 Institute for Pattern Recognition and Artificial IntelligenceHuazhong University of Science and Technology National Laboratory for Multi-Spectral Information Processing Technology Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics

A 128× 128 elements cylindrical liquid crystal （LC） lens array with electrically controllable focal length is proposed. The cylindrical LC lens array uses transparent indium tin oxide （ITO） films as electrode, avoiding to affect the optical path operating in the voltage-off status. As the top electrode of the cylindrical LC lens array contacts with LC, the operation voltage root-mean-square （RMS） amplitude can be as low as 1.4 V and the response time is about 20-30 ms. The special optical focusing feature of the cylindrical LC lens array is got. And the focal length of this array is about 60-450 μm.

关键词： Focusing ITO glass Liquid crystals Oxide films Tin Titanium compounds

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Pulsar/CNS integrated navigation based on federated UKF

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Journal of Systems Engineering and Electronics 2010年第4期21卷 675-681页

作者： Jin Liu Jie Ma Jinwen Tian State Key Laboratory for Multi-spectral Information Processing Technologies Institue for Pattern Recognition and artifical Intelligence Huazhong University of Science and Technology Wuhan 430074 P. R. China

In order to improve the autonomous navigation capability of satellite,a pulsar/CNS（celestial navigation system） integrated navigation method based on federated unscented Kalman filter（UKF） is *** celestial navigation is a mature and stable navigation ***,its position determination performance is not satisfied due to the low accuracy of horizon *** pulsar navigation is a new navigation method,which can provide highly accurate range *** major drawback of single pulsar navigation is that the system is completely *** two methods are complementary to each other,the federated UKF is used here for fusing the navigation data from single pulsar navigation and *** to the traditional celestial navigation method and single pulsar navigation,the integrated navigation method can provide better navigation *** simulation results demonstrate the feasibility and effectiveness of the navigation method.

关键词： autonomous navigation celestial navigation system（CNS） pulsar federated unscented Kalman filter（UKF）.

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Predicting functional impact of single amino acid polymorphisms by integrating sequence and structural features

Predicting functional impact of single amino acid polymorphi...

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IEEE International Conference on Systems Biology

作者： Mingjun Wang Hong-Bin Shen Tatsuya Akutsu Jiangning Song State Engineering Laboratory for Industrial Enzymes Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences (CAS) Tianjin China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Bioinformatics Center Institute for Chemical Research Kyoto University Uji Kyoto Japan Department of Biochemistry and Molecular Biology Faculty of Medicine Monash University Melbourne VIC Australia

Single amino acid polymorphisms (SAPs) are the most abundant form of known genetic variations associated with human diseases. It is of great interest to study the sequence-structure-function relationship underlying SAPs. In this work, we collected the human variant data from three databases and divided them into three categories, i.e. cancer somatic mutations (CSM), Mendelian disease-related variant (SVD) and neutral polymorphisms (SVP). We built support vector machine (SVM) classifiers to predict these three classes of SAPs, using the optimal features selected by a random forest algorithm. Consequently, 280 sequence-derived and structural features were initially extracted from the curated datasets from which 18 optimal candidate features were further selected by random forest. Furthermore, we performed a stepwise feature selection to select characteristic sequence and structural features that are important for predicting each SAPs class. As a result, our predictors achieved a prediction accuracy (ACC) of 84.97, 96.93, 86.98 and 88.24%, for the three classes, CSM, SVD and SVP, respectively. Performance comparison with other previously developed tools such as SIFT, SNAP and Polyphen2 indicates that our method provides a favorable performance with higher Sensitivity scores and Matthew's correlation coefficients (MCC). These results indicate that the prediction performance of SAPs classifiers can be effectively improved by feature selection. Moreover, division of SAPs into three respective categories and construction of accurate SVM-based classifiers for each class provides a practically useful way for investigating the difference between Mendelian disease-related variants and cancer somatic mutations.

关键词： Support vector machines Accuracy Proteins Feature extraction Humans Amino acids Databases

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Optimal ν-SVM parameter estimation using multi objective evolutionary algorithms

Optimal ν-SVM parameter estimation using multi objective ev...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

作者： Ethridge, James Ditzler, Gregory Polikar, Robi Dept. of Electrical and Computer Engineering Rowan University Signal Processing and Pattern Recognition Laboratory Glassboro NJ 08028 United States

ISBN: (纸本)9781424469109

Using a machine learning algorithm for a given application often requires tuning design parameters of the classifier to obtain optimal classification performance without overfitting. In this contribution, we present an evolutionary algorithm based approach for multi-objective optimization of the sensitivity and specificity of a ν-SVM. The ν-SVM is often preferred over the standard C-SVM due to smaller dynamic range of the ν parameter compared to the unlimited dynamic range of the C parameter. Instead of looking for a single optimization result, we look for a set of optimal solutions that lie along the Pareto optimality front. The traditional advantage of using the Pareto optimality is of course the flexibility to choose any of the solutions that lies on the Pareto optimality front. However, we show that simply maximizing sensitivity and specificity over the Pareto front leads to parameters that appear to be mathematically optimal yet still cause overfitting. We propose a multiple objective optimization approach with three objective functions to find additional parameter values that do not cause overfitting. © 2010 IEEE.

关键词： Multiobjective optimization

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Research on the method of medium wave infrared simulation based on Vega

Research on the method of medium wave infrared simulation ba...

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International Conference on Multimedia Technology

作者： Wang, Man Zhang, Tianxu State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424478743

Visual Simulation, which has been applied widely to provide convenience to people from every walk of life, plays a crucial role in the field of Virtual Reality. In this thesis, 8 models representing 8 typical materials, are created by MultiGen Creator, and rendered by Vega for analysis of relation between grey values in simulated pictures and real radiance. Finally, the method of infrared simulation based on Vega is proved effective in the field of military by comparison between simulated pictures and real shot pictures at different times of the day. ©2010 IEEE.

关键词： Virtual reality

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A novel automatic motion segmentation method based on optical flow

A novel automatic motion segmentation method based on optica...

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International Conference on Multimedia Technology

作者： Lu, Haifeng Zhang, Tianxu Yao, Cong State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424478743

Motion segmentation is one of the fundamental problems in digital image processing area. The estimation of velocity field is one of the most notable approaches on the first step of motion segmentation. A novel motion segmentation method is proposed, which is nonparametric and automatically selects value of the segmentation criterion. In particular, we first employ the optical flow to estimate the motion field;then we establish a segmentation criterion and measure the difference between regions of the moving objects and background separated in the segmentation criterion at each level;next we adopt the level of the segmentation criterion which makes the two regions the most different;finally, our approach output regions of moving objects and background from the scene. Experimental results demonstrate that our method is effective, and the procedure is much simpler than the methods often used. ©2010 IEEE.

关键词： Optical flows

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A high performance fully pipelined architecture for lossless compression of satellite image

A high performance fully pipelined architecture for lossless...

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2010 International Conference on Multimedia Technology, ICMT 2010

作者： Wang, Ze Zhang, Tianxu Yan, Luxin Gong, Cheng State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424478743

This paper presents a novel hardware implementation of the adaptive JPEG-LS in field programmable gate array (FPGA), based on the low complexity lossless compression for images (LOCO-I) compression scheme. Differently from what previously reported in literature, this design achieves a much lower complexity and super high data throughput through an improved prediction model by breaking the feedback loop of context parameters updating. The processing speed of this design is up to 75Mpixels per second, while the compression ratio is slightly lower than the standard JPEG-LS compression. Performance evaluation also indicates that design complexity and compression efficiency can be taken account at the same time to achieve satisfactory result. Such an implementation could be used for high-speed compression of satellite remote sensing image onboard. ©2010 IEEE.

关键词： Image compression

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A method of ground-based space object opho-electronic imaging simulation

A method of ground-based space object opho-electronic imagin...

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International Conference on Multimedia Technology

作者： Zhang, Putao Zhang, Tianxu State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424478743

It is very necessary to observe, tracking and recognise interested space object including space debris around the earth. A simulation method about ground-based sensor observing, tracking and imaging space object is researched. It includes the visibility analysis of space object in the STK scene, the attitude description mode of object, the data alternant form and format between STK and Vega, the imaging method of the object through Vega and the visual realization of the process. ©2010 IEEE.

关键词： Space debris

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Kernel ICA applied to feature extraction for image annotation

Kernel ICA applied to feature extraction for image annotatio...

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2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10

作者： Xu, Bingxin Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9781424481354

In automatic image annotation, it is often extracting low-level visual features from original image for the purpose of mapping to high level image semantic information. In this paper, we propose a novel method which integrates kernel independent component analysis (KICA) and support vector machine (SVM) for analyzing the semantic information of natural images. KICA, which contains a nonlinear kernel mapping component, is adopted to extract low-level features from the original image data. Then these feature vectors are mapped to high-level semantic words using SVM to annotate images with labels in a given semantic label set. Comparative studies have done for the performance of KICA with traditional color histogram and discrete cosine transform features. The experimental results show that the proposed method is capable of extracting the components of images as key features, and with these features to map into semantic categories, higher accuracy is achieved. © 2010 IEEE.

关键词： Support vector machines

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Feature data optimization with LVQ technique in semantic image annotation

Feature data optimization with LVQ technique in semantic ima...

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2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10

作者： Jiang, Ziheng He, Jing Guo, Ping School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)9781424481354

In order to improve the classifier performance in semantic image annotation, we propose a novel method which adopts learning vector quantization (LVQ) technique to optimize low level feature data extracted from given image. Some representative vectors are selected with LVQ to train support vector machine (SVM) classifier instead of using all feature data. Performance is compared between the methods with and without feature data optimization when SVM is applied to semantic image annotation. Experiment results show that the proposed method has a better performance than that without using LVQ technique. © 2010 IEEE.

关键词： Support vector machines

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