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International Conference on intelligent Transportation

作者： Mingxia Sun Kunfeng Wang Ming Tang Fei-Yue Wang Jinfeng Yang Tianjin Key Laboratory of Advanced Signal Processing Civil Aviation University of China Tianjin China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences (CAS) Beijing China

This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image, assuming moving vehicles may cause pixel intensities and local texture to change, and then by identifying such pixel changes to detect vehicles. In this research, multiple pattern classifiers including LDA + Adaboost, SVM, and Random Forests are used to detect vehicles that are passing through virtual loops. We extract fourteen pattern features (related to foreground area, texture change, and luminance and contrast in the local virtual loop zone and the global image) to train pattern classifiers and then detect vehicles. As experimental results illustrate, the proposed approach is quite robust to detect vehicles under complex dynamic environments, and thus is able to improve the accuracy of traffic data collection in all weather for long term.

关键词： Vehicles Feature extraction Training image edge detection Vehicle detection Meteorology Radio frequency

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Ultrasound image Denoising with Multi-shape Patches Aggregation Based Non-local Means

Ultrasound Image Denoising with Multi-shape Patches Aggregat...

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Wanjun Chen Mingyue Ding Yalin Miao Lei Luo Department of Information Science Xi'an University of Technology Xi'an Shaanxi China College of Life Science and Technology lmage processing and Intelligent Control key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China

The Non-Local Means (NLM) filter uses the redundancy of information in the image to remove noise, this scheme gives some of the best results among other powerful methods such as wavelet based approaches or diffusion techniques. Though simple to implement and efficient in practice, the classical NLM suffers from ringing artifacts around edges when using square patches, due to an abrupt lack of redundancy of the image. This paper presents an extended NLM based on Multi-Shape Patches Aggregation (NLM-MSPA) to overcome this problem, and uses it to remove medical ultrasound images corrupted by multiplicative speckle noise. We have incorporated a preprocessing step to make the speckle noise much closer to the real additive white Gaussian noise, hence more amenable to a denoising algorithm such as NLM-MSPA. Results on real images and artificially speckled images show that the proposed scheme outperforms several classical methods chosen for comparison in its ability to reduce speckle and preserve edge details.

关键词： Speckle Ultrasonic imaging Noise reduction Shape Biomedical imaging Signal to noise ratio

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Recognition of steel billet image with different orientations in production line

Recognition of steel billet image with different orientation...

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2010 International Conference on Optoelectronics and image processing, ICOIP 2010

作者： Zhang, Xiuhua Yang, Yijun Hong, Hanyu Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9780769542522

An automatic recognition method for steel billet images with different orientations is proposed in this paper. A crucial part of this method is to segment the image firstly, and then use the projection features of the segmented image to distinguish the different orientations of the steel billet in production line. After the string is segmented into individual characters, the segmented characters can be recognized by template matching. Experiments on steel billet image recognition demonstrate that the proposed method can distinguish the steel billet image orientation and recognize the characters automatically, which shows the effectiveness of the proposed method. © 2010 IEEE.

关键词： image recognition

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Voxel based treatment prediction using diffusion anisotropy indices and spatial information in Glioblastoma Multiform tumor

Voxel based treatment prediction using diffusion anisotropy ...

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Iranian Conference of Biomedical Engineering (ICBME)

作者： Hadi Sabahi Hamid Soltanian-Zadeh Lisa Scarpace Tom Mikkelsen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI USA

In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatment response of each tumor voxel. These DAIs are Fractional Anisotropy, Mean Diffusivity, Relative Anisotropy, and Volume Ratio, extracted from Diffusion Tensor Imaging (DTI) data before treatment. The spatial information is considered as the distance of each tumor voxel from the tumor center, extracted from pre-treatment post-contrast T1-weighted Magnetic Resonance images (pc-T1-MRI). DAIs and spatial information of each tumor voxel are considered as feature vector. DTI and pc-T1-MRI are gathered before and after the treatment of seven GBM patients. First, DAIs of all brain voxels and the distance of each tumor voxel from the tumor center are calculated. Second, the method registers pre-treatment DAI maps and post-treatment pc-T1-MRI to pre-treatment pc-T1-MRI. Next, the tumor is segmented using thresholding technique from pc-T1-MRI. Then, Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI are compared to label the feature vectors. Three classifiers were evaluated, including Support Vector Machine, K-Nearest Neighbor, and Artificial Neural Network. Classification results show a preference for K-Nearest Neighbor based on well-established performance measures.

关键词： Tumors Anisotropic magnetoresistance Diffusion tensor imaging Support vector machines Feature extraction Artificial neural networks

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One-time-pads encryption in the tile assembly model

One-time-pads encryption in the tile assembly model

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作者： Chen, Zhihua Xu, Jin Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Recent research has demonstrated that the ultra-scale computation by self-assembly DNA tiles can be implemented in the laboratory. One of the significant applications is the DNA-based cryptography systems. In this paper, we detail procedures for the DNA-based One-Time-Pads (OTP) cryptography, which is in principle unbreakable. In order to implement the whole encrypting and decrypting processes, we propose four tile systems: encrypting system, ciphertext extracting system, key extracting system and decrypting system. All the tile systems use θ(1) input tiles and compute in θ(n) steps according to the length of the input massage. The method of implementing the DNA OTP encryption extends the self-assemble tile models and achieves the real randomness in the DNA OTP. Copyright © 2010 American Scientific Publishers. All rights reserved.

关键词： Cryptography

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PARTICLE SWARM OPTIMIZATION（PSO）OF POWER ALLOCATION IN COGNITIVE RADIO SYSTEMS WITH INTERFERENCE CONSTRAINTS

PARTICLE SWARM OPTIMIZATION（PSO）OF POWER ALLOCATION IN COG...

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2011 4th IEEE International Conference on Broadband Network and Multimedia Technology

作者： Saeed Motiian Mohammad Aghababaie Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Colleague of EngineeringUniversity of TehranTehran 14399-57131Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences(IPM)Tehran 19548-56316 Iran Image Analysis Laboratory Radiology DepartmentHenry Ford HospitalDetroitMichigan 48202USA

Cognitive radio is used for enhancement of spectrum *** many works have been accomplished on the power allocation of cognitive radio,limited efforts have considered evolutionary *** this paper,we study this problem in the cognitive radio networks where interference constraints are defined for protection of quality of service（QoS）for both primary and secondary *** defined as functions of the signal-to-interference-plus-noise ratio（SINR） are matched for each secondary user which meets Nash’s *** general,the region of utilities that meets the constraints is *** is possible to make simplifications,generate a convex region,and then use common convex optimization approaches to obtain a ***,Particle Swarm Optimization（PSO）does not need such simplifications and thus its results are superior to those of the convex optimization *** is an evolutionary algorithm based on social intelligence,utilized in many optimization *** is a global optimizations algorithm that does not require the objective function be differentiable as required in classic optimization methods.

关键词： Cognitive radio Power allocation Particle Swarm Optimization（PSO）.

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Small universal spiking neural p systems with exhaustive use of rules

Small universal spiking neural p systems with exhaustive use...

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作者： Zhang, Xingyi Jiang, Yun Pan, Linqiang Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

We consider the problem of looking for small universal spiking neural P systems with exhaustive use of rules, which was formulated as an open problem by Andrei PǍun and Gheorghe PǍun in a survey paper. Here, spiking neural P systems are used in two versions: as devices computing functions and as devices generating sets of numbers, with two ways of encoding the result of a computation. As devices of computing functions, if we associate the result with the distance between the first two spikes emitted by the output neuron, we produce a universal computing spiking neural P system with exhaustive use of rules (without delay) having 125 neurons;if we introduce the usual way of defining the result of a computation in membrane systems to encode the result, namely, the number of spikes emitted during a computation, then a universal computing system (without delay) with 126 neurons is also obtained in the sense of the exhaustive use of rules. For spiking neural P systems used as generators of sets of numbers, we construct a universal system (without delay) by using 128 neurons under the first way of defining the computation result, and a system (without delay)by using127 neurous under the second way of defining the comutation result. Copyright © 2010 American Scientific Publishers. All rights reserved.

关键词： Neurons

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A note on small universal spiking neural P systems

A note on small universal spiking neural P systems

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10th International Workshop on Membrane Computing, WMC 2009

作者： Pan, Linqiang Zeng, Xiangxiang Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)3642114660

In the "standard" way of simulating register machines by spiking neural P systems (in short, SN P systems), one neuron is associated with each instruction of the register machine that we want to simulate. In this note, a new way is introduced for simulating register machines by SN P systems, where only one neuron is used for all instructions of a register machine;in this way, we can use less neurons to construct universal SN P systems. Specifically, a universal system with extended rules (without delay) having 10 neurons is constructed. © 2010 Springer-Verlag.

关键词： Neurons

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Small universal asynchronous spiking neural P systems

Small universal asynchronous spiking neural P systems

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Pan, Linqiang Zeng, Xiangxiang Zhang, Xinyi Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9781424464388

Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, this topic started to be considered also in the framework of (synchronized) spiking neural P systems. In this work, it is focused on small universal spiking neural P systems working in a non-synchronized manner. Specifically, it is proved that there is an asynchronous spiking neural P system with 76 neurons that is equivalent to a universal register machine for computing functions. As generator of sets of numbers, a universal asynchronous spiking neural P system with 75 neurons is constructed. © 2010 IEEE.

关键词： biocomputing computer science neural chips small universal computing devices universal asynchronous spiking neural P system universal register machine

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Degradation of AlGaN/GaN High Electron Mobility Transistors with Different AlGaN Layer Thicknesses under Strong Electric Field

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Chinese Physics Letters 2010年第2期27卷 243-245页

作者：杨凌马晶晶朱诚郝跃马晓华 Key Laboratory of Wide Band Gap Semiconductor Material and Device Institute of Microelectronics Xidian University Xi'an 710071 Key Laboratory of Intelligent Perception and Image Understanding (Ministry of Education) Institute of Intelligent Information Processing Xidian University Xi'an 710071 National Key Laboratory of Science and Technology on Antennas and Microwaves Xidian University Xi'an 710071

The degradation of AlGaN/GaN high electron mobility transistors （HEMTs） has a close relationship with a model of traps in AlGaN barriers as a result of high electric field. We mainly discuss the impacts of strong electrical field on the AlGaN barrier thickness of AlGaN/GaN HEMTs. It is found that the device with a thin AlGaN barrier layer is more easily degraded. We study the degradation of four parameters, i.e. the gate series resistance RGate, channel resistance R channel, gate current IG,off at VGS=-5 and VDS=0.1 V, and drain current ID,max at VGS=2 and VDS=5 V. In addition, the degradation mechanisms of the device electrical parameters are also investigated in detail.

关键词： Chinese climate network complex systems small world community

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