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Temporal pattern recognition using spiking neural networks for cortical neuronal spike train decoding

IFAC Proceedings Volumes 2008年第2期41卷 5203-5208页

作者： Huijuan Fang Yongji Wang Jiping He Shan Liu Key Laboratory for Image Processing and Intelligent Control of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China (Tel: 86-27-87557284 The Harrington Department of Bioengineering and the Center for Neural Interface Design of The Biodesign Institute Arizona State University Tempe AZ 85287 USA

Most experimental and decoding algorithm studies of brain neural signals assume that neurons transmit information as a rate coding, but recent studies on the fast cortical computations indicate that temporal coding is probably a more biologically plausible scheme used by neurons. We introduce spiking neural networks (SNN) which consist of spiking neurons propagate information by the timing of spikes to analyze the cortical neural spike trains directly without temporal information lost. The SNN based temporal pattern classification is compared with the conventional artificial neural networks (ANN) based firing rate analysis. The results show that the SNN algorithm can achieve higher accuracy, which demonstrates that temporal coding is a viable code for fast neural information processing and the SNN approach is suitable for recognizing the temporal pattern in the cortical neural signals.

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image denoising algorithm based on noise detection

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Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence 2008年第3期21卷 298-302页

作者： Jin, Liang-Hai Li, De-Hua State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Technol. Wuhan 430074 China

An efficient image denoising algorithm is introduced. Firstly, image pixels are classified into noisy pixels and noise-free pixels by four directional operators. Then an adaptive weighted median filter is designed to remove and restore the detected noisy pixels and keep the noise-free ones unchanged. Experimental results indicate that the proposed algorithm preserves image details well while removing impulsive noise efficiently, and its filtering performance is significantly superior to the classical median filter and some other typical and recently developed improved median filters.

关键词： Median filters

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Design of a PSO Based Fuzzy Logic controller for Vessel Mooring Shifting System

Design of a PSO Based Fuzzy Logic Controller for Vessel Moor...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Zhen Huang Yongji Wang Department of Control Science and Engineering HuaZhong University of Science and Technology Wuhan Hubei China School of Automation Wuhan University of Technology Wuhan Hubei China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Department of Control Science andEngineering Huazhong University of Science슠and슠Technology Wuhan Hubei China

A fuzzy logic controller (FLC) is designed to achieve course-keeping for mooring shifting system, which is the main system of non self-propelled vessels. Compared with manual operation, the automatic operation and monitoring system with the FLC can perform higher precision and efficiency. The particle swarm optimization (PSO) algorithm is introduced to optimize the proposed FLCpsilas parameters. A series of simulation studies have been undertaken to compare the performance of a basis FLC and PSO based FLC. The results demonstrate that the latter has the better controlling quality.

关键词： Fuzzy logic control systems Automatic control Particle swarm optimization Fuzzy systems Design engineering Knowledge engineering Design automation Manuals Computerized monitoring

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Computer aided diagnosis of fatty liver ultrasonic images based on support vector machine

Computer aided diagnosis of fatty liver ultrasonic images ba...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Guokuan Li Yu Luo Wei Deng Xiangyang Xu Aihua Liu Enmin Song School of Computer Science and Technology Key Laboratory for Image Processing & Intelligent Control of Ministry of Education Huazhong University of Science and Technology Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology China Ultrasound Department Sixth Hospital of Wuhan City China

B-scan ultrasound is the primary means for the diagnosis of fatty liver. However, due to use of various ultrasound equipments, poor quality of ultrasonic images and physical differences of patients, fatty liver diagnosis is mainly qualitative, and often depends on the subjective judgment of technicians and doctors. Therefore, computer-aided feature extraction and quantitative analysis of liver B-scan ultrasonic images will help to improve clinical diagnostic accuracy, repeatability and efficiency, and could provide a measure for severity of hepatic steatosis. This paper proposed a novel method of fatty liver diagnosis based on liver B-mode ultrasonic images using support vector machine (SVM). Fatty liver diagnosis was transformed into a pattern recognition problem of liver ultrasound image features. According to the different characteristics of fatty liver and healthy liver, important image features were extracted and selected to distinguish between the two categories. These features could be represented by near-field light-spot density, near-far-field grayscale ratio, grayscale co-occurrence matrix, and neighborhood gray-tone difference matrix (NGTDM). A SVM classifier was modeled and trained using the clinical ultrasound images of both fatty liver and normal liver. It was then exploited to classify normal and fatty livers, achieving a high recognition rate. The diagnostic results are satisfactorily consistent with those made by doctors. This method could be used for computer-aided diagnosis of fatty liver, and help doctors identify the fatty liver ultrasonic images rapidly, objectively and accurately.

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Face recognition under variable lighting using local qualitative representations

Face recognition under variable lighting using local qualita...

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MIPPR 2007: Pattern Recognition and Computer Vision

作者： Zhang, Yi Chu, Ying Mou, Xingang Zhang, Guilin State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819469526

In this paper, a face recognition method using local qualitative representations is proposed to solve the problem of face recognition in varying lighting. Based on the observation that the ordinal relationship between the average brightness of image regions pair is invariant under lighting changes, Local Binary Mapping is defined as an illumination invariant for face recognition based on Local Binary Pattern descriptor, which extracts the local variance features of an image. For the 'symbol' feature vector, hamming distance is used as similarity measurement. It has been proved that the proposed method can provide the accuracy of 100 percent for subset 2, 3, 4 and 98.89 percent for subset 5 of the Yale facial database B when all images in subset 1 are used as gallery.

关键词： Face recognition

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image fusion algorithm using nonsubsampled contourlet transform

Image fusion algorithm using nonsubsampled contourlet transf...

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MIPPR 2007: Multispectral image processing

作者： Yang, Xiao Zhiguo, Cao Kai, Wang Zhengxiang, Xu Institute of Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong Uni. of Sci. and Tech. Wuhan 430074 China

ISBN: (纸本)9780819469519

In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for image fusion. Each image from different sensors could be decomposed into a low frequency image and a series of high frequency images of different directions by multi-sacle NSCT. For low and high frequency images, they are fused based on local-contrast enhancement and definition respectively. Finally, fused image is reconstructed from low and high frequency fused images. Experiment demonstrates that NSCT could preserve edge significantly and the fusion rule based on region segmentation performances well in local-contrast enhancement.

关键词： image fusion

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IHS and support value integrated approach to improve pansharpening quality of QuickBird image

IHS and support value integrated approach to improve panshar...

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MIPPR 2007: Multispectral image processing

作者： Zheng, Sheng Yang, Changeai Liu, Jian Tian, Jinwen Electronics and Information Engineering Department Huazhong University of Science and Technology Wuhan 430074 China Institute of Intelligent Vision and Image Information Best College of Electrical Engineering and Information Technology China Three Gorges University Yichang 443002 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819469519

image fusion is an important tool in remote sensing, since many Earth observation satellites provide both high-resolution panchromatic (Pan) and low-resolution multispectral (MS) images. To date, many image fusion techniques have been developed. However, the available algorithms can hardly produce a satisfactory fusion result for IKONOS and QuickBird images. Among the existing fusion algorithms, the IHS technique is the most widely used one, and the wavelet fusion is the most frequently discussed one in recent publications because of its advantages over other fusion techniques. But the color distortion of these two techniques is often obvious. The support value fusion technique demonstrates some advantages over the conventional methods. This study presents a new fusion approach that integrates the advantages of both the IHS and the support value techniques to reduce the color distortion of QuickBird fusion results. Different QuickBird images have been fused with this new approach. Visual and statistical analyses prove that the concept of the proposed extended fast IHS (eFIHS) and support value integration is promising, and it does significantly improve the fusion quality compared to conventional IHS (eFIHS) and wavelet fusion techniques.

关键词： image fusion

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Robotic dynamic target recognition and tracking based on the monocular vision

Robotic dynamic target recognition and tracking based on the...

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26th Chinese control Conference, CCC 2007

作者： Lei, Liu Yongji, Wang Huazhong University of Science and Technology Intelligent and Complex System Laboratory Key Laboratory of Image Processing and Intelligent Control Ministry of Education

ISBN: (纸本)7900719229

Gather the information of the environment by the monocular vision. Using the H and S weight of the HSV color model, separate the target from the environment with a certain color, by a fast clustering algorithm for two-value image segmentation. Calculating the distance between the camera and target by the 3D reconstruction algorithm and sub-control strategy, and raise its veracity by laser information fusion. Furthermore, a vision servo system has been designed and utilized to achieve the robot's dynamic track. At last, some experiments were used to certification its availability.

关键词： Robot applications

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AN IKONOS image FUSION PROCESS USING SUPPORT VALUE TRANSFORM

AN IKONOS IMAGE FUSION PROCESS USING SUPPORT VALUE TRANSFORM

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2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： SHENG ZHENG WENZHONG SHI JIAN LIU Institute of Intelligent Vision and Image Information Best College of Electrical Engineering and In Advanced Research Center for Spatial Information Technology Department of Land Surveying and Geo-In State Education Commission Key Lab for Image Processing and Intelligent Control HUST Wuhan 430074

Panchromatic (Pan)-sharpening of multispectral (MS) bands is an important technique in various applications of satellite remote *** this paper, we apply the support value transform (SVT) to Ikonos image *** fused saliency features are represented by support values and extracted by *** low-resolution MS bands are resampled to the fine scale of the Pan image and sharpened by injecting the detailed features extracted from the high-resolution Pan *** fusing results on Ikonos MS + Pan data demonstrate that the proposed image fusion method is effective and efficient.

关键词： Mapped least squares support vector machine (mapped LS-SVM) support value transform (SVT) Ikonos image fusion

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EDGE DETECTION USING SUPPORT VALUE TRANSFROM

EDGE DETECTION USING SUPPORT VALUE TRANSFROM

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2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： SHENG ZHENG JINWEN TIAN JIAN LIU Electronics and Information Engineering Department Huazhong University of Science and Technology W State Education Commission Key Lab for Image Processing and Intelligent Control HUST Wuhan 430074 Electronics and Information Engineering Department Huazhong University of Science and Technology W

An innovative edge detection algorithm using the support value transform is presented in this *** on the support value transform, the multi scale support value images are extracted from the *** resolution of an image is directly related to the proper scale for edge detection, and the second level support value image is used to locate the edge positions by their zero *** experiments are carried out and sharp image edges are obtained from a variety of sample *** with many other existing methods, including LoG and Canny detectors, the proposed algorithm is superior to the LOG and Roberts approach.

关键词： Edge detection mapped least squares support vector machine (mapped LS-SVM) support value transform (SVT) zero crossings

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