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检索条件"机构=Key Laboratory of Image Processing and Intelligent"

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Spiking neural P systems for arithmetic operations

Spiking neural P systems for arithmetic operations

引用

6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011

作者： Zeng, Xiangxiang Song, Tao Pan, Linqiang Zhang, Xingyi Key Laboratory on Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab of Intelligent Computing and Signal Processing School of Computer Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9780769545141

Recently, Gutiérrez-Naranjo and Leporati considered performing basic arithmetic operations on a new class of bioinspired computing devices - spiking neural P systems (for short, SN P systems). However, the binary encoding mechanism used in their research looks like the encoding approach in electronic circuits, instead of the style of spiking neurons (in usual SN P systems, information are encoded as the time interval between spikes). In this work, three SN P systems are constructed as adder, subtracter and multiplier, respectively. In these devices, a number is inputted to the system as the interval of time elapsed between two spikes received by input neuron, the result of a computation is the time between the moments when the output neuron spikes. © 2011 IEEE.

关键词： Encoding (symbols)

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NEAT versus PSO for evolving autonomous multi-agents coordination on pursuit-evasion problem

NEAT versus PSO for evolving autonomous multi-agents coordin...

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2011 3rd International Asia Conference on Informatics in Control, Automation and Robotics, CAR 2011

作者： Zhao, Jin Peng, Gang Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry China

ISBN: (纸本)9783642259913

A method based on multi-agents and ANN (Artificial Neural Network) was proposed to solve the pursuit-evasion task in continuous time-varying environment. According to this method, several autonomous agents with 8 circular sector sensors and an ANN controller were used to form a coordinated behavior to capture the evaders. To evolve the controller, NEAT (NeuroEvolution of Augmenting Topologies) and PSO (Particle Swarm Optimization) method were used to optimize the network. The simulation experiments show that both methods can successfully evolve the controller to capture the evaders, while NEAT requires less swarm members and consume less time comparing to PSO method. © 2011 Springer-Verlag.

关键词： Controllers

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3D ultrasound data acqusition system based on back end scan mode

3D ultrasound data acqusition system based on back end scan ...

引用

2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Qi, Jian Ding, Mingyue Yuchi, Ming Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

The data acquisition of 3D-Ultrasound includes array scan and mechanical scan, and the later one is more easy to realize. Currently, the traditional probe scanning mode is Front-end scanning. Under the above scanning mode, when it scans over the breast, 2D-Ultrasound probe slides through the surface of the patients' bodies, the image will be influenced strongly by the human *** this paper we propose a new scanning mode to solve the above problem: Back-End scan, the back end rotates while the front end contacts the patients' skin without slide. The device designed using dual stepper motors which are under the synchronization control. Experiment results show the effectiveness of the proposed device. © 2011 IEEE.

关键词： Scanning

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Saliency Model Based Head Pose Estimation by Sparse Optical Flow

Saliency Model Based Head Pose Estimation by Sparse Optical ...

引用

第一届亚洲模式识别会议

作者： Chao Wang Tao Xu Yunhong Wang Zhaoxiang Zhang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

Head pose plays an important role in Human- Computer interaction, and its estimation is a challenge problem compared to face detection and recognition in computer vision. In this paper, a novel and efficient method is proposed to estimate head pose in real-time video sequences. A saliency model based segmentation method is used not only to extract feature points of face, but also to update and rectify the location of feature points when missing happened. This step also gives a benchmark for vector generation in pose estimation. In subsequent frames feature points will be tracked by sparse optical flow method and head pose can be determined from vectors generated by feature points between successive frames. Via a voting scheme, these vectors with angle and length can give a robust estimation of the head pose. Compared with other methods, annotated training data set and training procedure is not essential in our method. Initialization and re-initialization can be done automatically and are robust for profile head pose. Experimental results show an efficient and robust estimation of the head pose.

关键词： Face Estimation Magnetic heads Optical imaging Computer vision Skin

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Interesting Region Detection in Aerial Video Using Bayesian Topic Models

Interesting Region Detection in Aerial Video Using Bayesian ...

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第一届亚洲模式识别会议

作者： Jiewei Wang Yunhong Wang Zhaoxiang Zhang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Searching interesting regions in aerial video is a new and challenging problem. This paper presents an approach to detect visual interesting regions in aerial video using pLSA topic model. Traditional interesting region detection approaches just use bottom-up information, such as color, orientation and movement etc. Our proposed method can discover the semantic content of the whole image, the co-occurrence of local image patches via pLSA model, and consequently improve detection result significantly in real world scenes. First, we extract frames from aerial video as documents. Then we use vector quantized SIFT descriptors as words. Third, we discover topics (e.g. plants, roads, buildings) and the relation among them using pLSA model. Finally, we can detect interesting regions as we need according to calculated models. Experimental observations show the success of our approach on interesting region detection in aerial video.

关键词： Visualization Histograms Detectors Semantics Observers Vectors Vocabulary

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Multi-view Moving Objects Classification via Transfer Learning

Multi-view Moving Objects Classification via Transfer Learni...

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第一届亚洲模式识别会议

作者： Jianyun Liu Zhaoxiang Zhang Yunhong Wang Yi Mo Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Moving objects classification in traffic scene videos is a hot topic in recent years. It has significant meaning to intelligent traffic system by classifying moving traffic objects into pedestrians, motor vehicles, non-motor vehicles etc.. Traditional machine learning approaches make the assumption that source scene objects and target scene objects share same distributions, which does not hold for most occasions. Under this circumstance, large amount of manual labeling for target scene data is needed, which is time and labor consuming. In this paper, we introduce TrAdaBoost, a transfer learning algorithm, to bridge the gap between source and target scene. During training procedure, TrAdaBoost makes full use of the source scene data that is most similar to the target scene data so that only small number of labeled target scene data could help improve the performance significantly. The features used for classification are Histogram of Oriented Gradient features of the appearance based instances. The experiment results show the outstanding performance of the transfer learning method comparing with traditional machine learning algorithm.

关键词： Feature extraction Training image edge detection Training data Accuracy Videos Support vector machines

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A Real Time Object Tracking Approach for Mobile Robot Visual Servo Control

A Real Time Object Tracking Approach for Mobile Robot Visual...

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第一届亚洲模式识别会议

作者： Zhaoxiang Zhang Yunhong Wang Ruhan Sa Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

A key problem of image Based Visual Servo (IBVS) System is to track objects in image sequences. Thus, the tracking algorithm plays an important role in improving the efficiency of IBVS systems. In this paper, a novel tracking algorithm called Modified CamShift Guided Particle Filter (MCAMSGPF) is proposed, which interpolated Speeded-Up Robust Features (SURF) into the framework of conventional CamShift Guided Particle Filter (CAMSGPF) tracking method. This new algorithm outperforms conventional CAMSGPF and other baseline trackers with respect to tracking robustness in the clutter background of similar colors and occlusions. We also proposed a new system model to implement and test the new algorithm in a real time moving IBVS system, which is applied in a mobile robot with an on-board camera.

关键词： Robustness image color analysis Robots Target tracking Cameras Clutter

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View-invariant Action Recognition in Surveillance Videos

View-invariant Action Recognition in Surveillance Videos

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第一届亚洲模式识别会议

作者： Fang Zhang Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Recently, human action recognition has been a popular and important topic in computer vision. However, except some conventional problems such as noise, low resolution etc., viewinvariant recognition is one of the most challenging problems. In this paper, we focus on solve multi-view action recognition from surveillance video. To detect moving objects from complicated backgrounds, this paper employs improved Gaussian mixed model, which uses K-means clustering to initialize the model and it gets better motion detection results for surveillance videos. We demonstrate the silhouette representation ”Envelope Shape” can solve the viewpoint problem in surveillance videos. The experiment results demonstrate that our human action recognition system is fast and efficient on CASIA activity analysis database.

关键词： Videos Gaussian distribution Surveillance Shape Humans Hidden Markov models Databases

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Research on fuzzy enhancement in the diagnosis of liver tumor from B-mode ultrasound images

Research on fuzzy enhancement in the diagnosis of liver tumo...

引用

2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Qiu, Wu Wang, Rui Xiao, Feng Ding, Mingyue School of Life Science and Technololgy Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)9780769546230

Fuzzy enhancement is applied in computer aided diagnosis of liver cancer from B mode ultrasound images as a pre-processing procedure in this paper. It was evaluated with three classifiers including K means, back propagation neural network and support vector machine using 25 features from first order statistic (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), Grey level dependant matrix (GLDM) and LAWS. In the analysis of 166 normal liver tissue, 30 hemangioma and 60 malignant tumor, our method improved the classification accuracy of three classifiers (K means, BP neural network and support machine vector) in distinguishing liver cancer, hemangioma and normal liver cancer from B mode ultrasound images. It is proved that fuzzy enhancement as an efficient preprocessing procedure could be used in the computer aided diagnosis system of liver cancer. © 2011 IEEE.

关键词： Support vector machines

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Deformation prediction of landslide based on genetic-simulated annealing algorithm and BP neural network

Deformation prediction of landslide based on genetic-simulat...

引用

4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Chen, Huangqiong Zeng, Zhigang Department of Control Science and Engineering Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China

ISBN: (纸本)9781612843735

In this paper, a modified method for landslide prediction is presented. This method is based on the back propagation neural network(BPNN), and we use the combination of genetic algorithm and simulated annealing algorithm to optimize the weights and biases of the network. The improved BPNN modeling can work out the complex nonlinear relation by learning model and using the present data. This paper demonstrates that the revised BPNN modeling can be used to predict and calculate landslide deformation, quicken the learning speed of network and improve the predicting precision. Applying this thinking and method into research of some landslide in the Three Gorges reservoir, the validity and practical value of this model can be demonstrated. And it also shows that the dynamic prediction of landslide deformation is very crucial. © 2011 IEEE.

关键词： Landslides

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