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A fast star pattern recognition algorithm based on feature vector

A fast star pattern recognition algorithm based on feature v...

引用

2010 international conference on Computer Design and Applications, ICCDA 2010

作者： Li, Qi-Shen Zhu, Chang-Ming Guan, Jun School of Information Engineering Nanchang Hangkong University Nanchang China

ISBN: (纸本)9781424471638

Stars in a star map can be regarded as a point pattern, and we can utilize the matching of point pattern to recognize the star pattern. First, the nth Radius-Weighted-Mean Points (RWMPs) are proposed which are invariant to translation, rotation and scaling, and then, a RWMP-based feature vector is constructed which is still invariant to translation and rotation. The candidate referenced star images and their corresponding attitudes are obtained by computing the Euclidean distance between the viewed star image and each of the star images in the pattern database. The verification process is introduced to confirm the identification results. The simulation results indicates that the average identification rate of this algorithm can be enhanced 3.5% as compared to the grid algorithm at the same position noise level from 0 to 3 pixels, and the identification time of the proposed algorithm reduces to 1/5. © 2010 IEEE.

关键词： Stars

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Recurrence Enhances the Spatial Encoding of Static Inputs in Reservoir Networks

Recurrence Enhances the Spatial Encoding of Static Inputs in...

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20th international conference on Artificial Neural Networks

作者： Emmerich, Christian Reinhart, Rene Felix Steil, Jochen Jakob Univ Bielefeld Res Inst Cognit & Robot CoR Lab D-33615 Bielefeld Germany

ISBN: (纸本)9783642158216

We shed light on the key ingredients of reservoir computing and analyze the contribution of the network dynamics to the spatial encoding of inputs. Therefore, we introduce attractor-based reservoir networks for processing of static patterns and compare their performance and encoding capabilities with a related feedforward approach. We show that the network dynamics improve the nonlinear encoding of inputs in the reservoir state which can increase the task-specific performance.

关键词： reservoir computing extreme learning machine static pattern recognition

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Human action recognition via multi-view learning 10

Human action recognition via multi-view learning

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Proceedings of the Second international conference on Internet Multimedia computing and Service

作者： Zhang, Tianzhu Liu, Si Xu, Changsheng Lu, Hanqing National Lab. of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China China-Singapore Institute of Digital Media Singapore 119613 Singapore

ISBN: (纸本)9781450304603

In this paper, we propose a novel approach to automatically learn a compact and yet discriminative representation for humane action recognition. Considering the static visual information and motion information, each frame is represented in two feature subsets (views) and Gaussian Mixture Model (GMM) is adopted to model the distributions of those features. In order to complement the strengths of the different features (views), a Co-EM based multiview learning framework is introduced to estimate the parameters of GMM instead of conventional single view based EM. Then Gaussian components are considered as video words to describe videos with different time resolutions. Compared with the traditional method to recognize action, there are several advantages with the proposed method using Co-EM strategy. First, complex actions are efficiently modeled by GMM, and the number of its component is automatically determined with the Minimum Description Length (MDL). Second, because the imperfectness of single view can be compensated by the other view in the Co-EM, the resulting bag of video words are superior to that formed by any single view. To the best of our knowledge, we are the first to try the Co-EM based multi-view learning method for action recognition and obtain significantly better results. We extensively verify our proposed approach on two publicly available challenging datasets: the KTH dataset and Weizmann dataset. The experimental results show the validity of our proposed method. Copyright 2010 ACM.

关键词： Gaussian distribution

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Parallel splicing on iso-arrays

Parallel splicing on iso-arrays

引用

2010 IEEE 5th international conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2010

作者： Masilamani, V. Christy, D.K. Sheena Thomas, D.G. Kalyani, T. Department of Computer Science and Engineering IIITD and M Chennai - 600036 India Department of Mathematics Jeppiaar Engineering College Chennai - 600119 India Department of Mathematics Madras Christian College Tambaram Chennai - 600059 India Department of Mathematics St. Joseph's College of Engineering Chennai - 600119 India

ISBN: (纸本)9781424464388

In this paper we introduce a new model called iso-picture splicing system, to generate iso-pictures. We compare the family of languages generated by the proposed system with existing family of languages such as local iso-picture languages and we prove some properties of the family of languages generated by proposed system. © 2010 IEEE.

关键词： DNA computing biocomputing iso-arrays iso-picture languages iso-picture splicing system local iso-picture languages parallel splicing pattern recognition splicing system

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Towards Spatio-Temporal pattern recognition Using Evolving Spiking Neural Networks

Towards Spatio-Temporal Pattern Recognition Using Evolving S...

引用

17th international conference on Neural Information Processing

作者： Schliebs, Stefan Nuntalid, Nuttapod Kasabov, Nikola Auckland Univ Technol KEDRI Auckland New Zealand

ISBN: (纸本)9783642175367

An extension of an evolving spiking neural network (eSNN) is proposed that enables the method to process spatio-temporal information. In this extension, an additional layer is added to the network architecture that transforms a spatio-temporal input pattern into a single intermediate high-dimensional network state which in turn is mapped into a desired class label using a fast one-pass learning algorithm. The intermediate state is represented by a novel probabilistic reservoir computing approach in which a stochastic neural model introduces a non-deterministic component into a liquid state machine. A proof of concept is presented demonstrating an improved separation capability of the reservoir and consequently its suitability for an eSNN extension.

关键词： Neural networks

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Water distribution network leakage analysis modeling based on pattern recognition theory

Water distribution network leakage analysis modeling based o...

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10th international conference on computing and Control for the Water Industry

作者： Wu, C. G. Liu, B. C. Yuan, Y. X. Pei, W. Z. Zhao, P. Wang, M. X. Yang, X. D. Harbin Inst Technol Sch Municipal & Environm Engn Harbin 150006 Heilongjiang Peoples R China Anshan Water Supply Gen Co Anshan Liaoning Peoples R China

ISBN: (纸本)9780415548519

Water leakage is now a serious widespread problem in water distribution network (WDN), no matter what pipe material it used, leakage will occur inevitably with time. Therefore, the problem of water leakage has become the focus of China's water supply industry. When leakage occurs, the values of the pressure at monitoring points will fluctuate which are relation with leakage degree or location. And it is just like the fingerprints by which software can identify a person. Therefore, in this paper, PNN (PNN) is provided for recognizing fluctuations caused by leakage so as to find the leakage locations approximately by the method of Bayesian classifier selector. The model is applied in water supply networks of a city located in Northeast of China, using its actual monitoring data to check the established leakage locating model. Then we analyzed the existing problems of model and proposed possible measures for leakage control of water industry.

关键词： pattern recognition

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Discovery of Gait Anomalies from Motion Sensor Data

Discovery of Gait Anomalies from Motion Sensor Data

引用

22nd international conference on Tools with Artificial Intelligence

作者： Pogorelc, Bogdan Gams, Matja Spica Int Doo Dept Intelligent Syst Jozef Stefan Inst Ljubljana Slovenia

ISBN: (纸本)9780769542638

A tool for discovery of gait anomalies of elderly from motion sensor data is proposed. The gait of the user is captured with the motion capture system, which consists of tags attached to the body and sensors situated in the apartment. Position of the tags is acquired by the sensors and the resulting time series of position coordinates are analyzed with dynamic time warping and machine learning algorithms in order to identify the specific gait anomaly. We designed medically oriented features for training a machine learning classifier that classifies the user's gait into: i) normal, ii) with hemiplegia, iii) with Parkinson's disease, iv) with pain in the back and v) with pain in the leg. Experimental results show that the proposed tool is usable for discovery of gait anomalies.

关键词： Parkinson disease biosensors data mining diseases dynamic time warping elderly gait analysis gait analysis gait anomaly geriatrics hemiplegia learning (artificial intelligence) leg pain machine learning classifier medical computing motion capture system motion recognition motion sensor data patient care pattern classification tag position

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Ubiquitous computing in Creation of Cognitive Systems for Medical Images Interpretation

Ubiquitous Computing in Creation of Cognitive Systems for Me...

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international conference on Ubiquitous computing and Multimedia Applications

作者： Ogiela, Lidia Ogiela, Marek R. Tadeusiewicz, Ryszard AGH Univ Sci & Technol Fac Management Al Mickiewicza 30 PL-30059 Krakow Poland AGH Univ Sci & Technol Inst Automat PL-30059 Krakow Poland

ISBN: (纸本)9783642134661

This publication discusses intelligent systems for cognitive data categorisation with a particular emphasis on image analysis systems used to analyse medical images. This type of systems used to interpret, analyse and reason work following the operating principles of cognitive information system. Cognitive systems interpret complex data by extracting semantic levels from it, which they use to determine the meaning of the data analysed, to cognitively understand it, as well as to reason and forecast changes in the area of the phenomena researched. Thus the course of human processes of leaning about the described phenomenon becomes the foundation for developing automatic cognitive systems which are called cognitive data analysis systems.

关键词： Cognitive processes cognitive information systems cognitive informatics graph image analysis pattern recognition UBIAS systems (Understanding Based Image Analysis Systems)

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Palmprint recognition combining LBP and cellular automata

Palmprint recognition combining LBP and cellular automata

引用

6th international conference on Intelligent computing, ICIC 2010

作者： Dai, Xiao Dong Wang, Bing Zhenwang, Pei Institute of Electrical and Information Anhui University of Technology Maanshan China

ISBN: (纸本)3642149219

In this paper, we present a palmprint recognition method which combines local binary pattern (LBP) and cellular automata. The LBP descriptor is proposed as a unifying texture model that describes the formation of a texture with micro-textons and their statistical placement rules. Because texture is one of the most importent features in palmprint image, so we think the features based on LBP will be good discriminative for palmprint identification. Cellular automata can be generally described as discrete dynamic systems completely defined by a set of rules in a local neighborhood. In this paper, we use cellular automata to extract features as the part of feature vector. The experiments conducted on Polytechnic University Palmprint Database I demonstrates the effectiveness of proposed method. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Local binary pattern

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2010 6th international conference on Wireless Communications, Networking and Mobile computing, WiCOM 2010

2010 6th International Conference on Wireless Communications...

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2010 6th international conference on Wireless Communications, Networking and Mobile computing, WiCOM 2010

ISBN: (纸本)9781424437092

The proceedings contain 1,072 papers. The topics discussed include: vehicle surface affection on antenna polarization;RBF intelligent model of microwave rectangular PDGS-LPF;printed 6-element dipole array antenna for omnidirection applied in WiMAX;an effective target tracking algorithm in infrared images video;residual-feedback particle filter for maneuvering target tracking;nonlinear analog circuit diagnosis based on Volterra series and neural network;simulation on the fast frequency estimation algorithm of FH signal;a new MMSE estimator based on signal correlation property;performance analysis and simulation of both QPSK and OQPSK;a review of adaptive beamforming techniques for wideband smart antennas;a practical and efficient algorithm for distributed interference alignment based on cognitive radio;the use of remote sensing technology in environmental protection;and research on pattern recognition based on the universal electronic tongue system.

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