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Research of characteristics extraction based on dynamic pressure signal

Research of characteristics extraction based on dynamic pres...

引用

3rd international conference on Intelligent Structure and Vibration Control, ISVC 2013

作者： Liu, Wei Liu, Hong Zhao School of Mechanical and Precision Instrument Engineering Xi'an University of Technology Xi'an 710048 China Computer Science and Technology Department Shaanxi Xueqian Normal University Xi'an 710061 China

ISBN: (纸本)9783037857236

The accuracy of pattern recognition was determined by the feature selection, and two methods of the characteristic description were discussed. The results show that the statistical characteristics could be used as a dynamic pressure signal descriptor, and the oscillation characteristic of curve is not suitable for describing dynamic pressure signal by itself. The selection of descriptors of dynamic pressure signal is the precondition to identify the leak signal and the non-leak signal effectively. © (2013) Trans Tech Publications, Switzerland.

关键词： pattern recognition

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Using LS-SVM pattern recognizer to detect change-point in ARMA process

Using LS-SVM pattern recognizer to detect change-point in AR...

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3rd international conference on Frontiers of Manufacturing and Design Science (ICFMD 2012)

作者： Cheng Zhiqiang North China Univ Water Resources & Elect Power Sch Management & Econ Zhengzhou 450011 Henan Peoples R China

ISBN: (纸本)9783037855782

Based on LS-SVM pattern recognizer, this paper develops an intelligent method for solving the problem of change-point detection, and the proposed model is applied to detect change-point of process mean-shift in auto-correlated time series process. In this research, LS-SVM algorithm and moving window method are used to detect the location of the mean shift signal, the LS-SVM pattern recognizer is designed and the performance of the recognizer is evaluated in terms of Accuracy Rate. Results of simulation experiment show that the proposed intelligent model is an effective method to detect change-point in ARMA data series.

关键词： change-points detection least squares support vector machine pattern recognition ARMA process

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Image Analysis - 18th Scandinavian conference, SCIA 2013, Proceedings

Image Analysis - 18th Scandinavian Conference, SCIA 2013, Pr...

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18th Scandinavian conference on Image Analysis, SCIA 2013

ISBN: (纸本)9783642388859

The proceedings contain 67 papers. The topics discussed include: texture description with completed local quantized patterns;a local image descriptor robust to illumination changes;detection of curvilinear structures by tensor voting applied to fiber characterization;simple-graphs fusion in image mosaic: application to automated cell files identification in wood slices;unsupervised segmentation of anomalies in sequential data, images and volumetric data using multiscale Fourier phase-only analysis;extended 3D Line Segments from RGB-d data for pose estimation;incorporating texture intensity information into LBP-based operators;Bayesian non-parametric image segmentation with Markov random field prior;evaluating local feature detectors in salient region detection;forest stand delineation using a hybrid segmentation approach based on airborne laser scanning data;and mean shift with flatness constraints.

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Influence of exceptional data on bridge damage assessment based on one-class SVM pattern recognition

Influence of exceptional data on bridge damage assessment ba...

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3rd international conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, CSC 2013

作者： Furuta, H. Nomura, Y. Nakatsu, K. Hattori, H. Yasuda, S. Faculty of Informatics Kansai University Japan Department of Science and Engineering Ritsumeikan University Japan Department of Modern Life Osaka Jonan Women's Junior College Japan Graduate School of Engineering Kyoto University Japan Graduate School of Informatics Kansai University Japan

ISBN: (纸本)9781905088584

Recently, it has become difficult to ensure the skill level of bridge maintenance engineers as a result of the retirement of experienced engineers. Hence, the daily inspection of bridges cannot be performed accurately and efficiently for the early detection of damage and to ensure appropriate measures. In previous research, damage assessment by introducing the technology of pattern recognition of digital images has been proposed. However, in the previous research, it was confirmed that there were some images which might be considered as exceptional data among the images of cracks of concrete decks. This paper describes the development of a support system for decision making in the damage assessment of bridges based on the pattern recognition by using the exception extraction. In this system, the exception extraction with one-class SVM removes some data that may cause the decrease of generalization capability of pattern recognition from the database. Thus, it may be expected that the accuracy and confidence of the results are improved. Numerical examples applying digital images of reinforced-concrete slabs of bridges with cracks are presented to demonstrate the practical use of the approach of this approach. ©Civil-Comp Press, 2013.

关键词： pattern recognition

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Protocol for Site Selection and Movement Assessment for the Myoelectric Control of a Multi-Functional Upper-Limb Prosthesis

Protocol for Site Selection and Movement Assessment for the ...

引用

35th Annual international conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Al-Timemy, Ali H. Escudero, Javier Bugmann, Guido Outram, Nicholas Univ Plymouth Sch Comp & Math Ctr Robot & Neural Syst Plymouth PL4 8AA Devon England

ISBN: (纸本)9781457702167

Although there have been many advances in electromyography (EMG) signal processing and pattern recognition (PR) for the control of multi-functional upper-limb prostheses, some the outstanding problems need to be solved before practical PR-based prostheses can be put into service. Some of these are the lack of training and deployment protocols and the provision of the tools required. Therefore, we present a preliminary procedure to personalize the prosthesis deployment. In the first step, we record the demographic information of each individual amputee person and their background. In the second step of the protocol, the EMG signals are acquired. PR algorithms and parameters will be chosen in the 3rd step of the protocol. In the 4th step, the best number of EMG sensors to achieve the maximal performance with a full set of gestures is identified. The final step involves finding the best set of movements that the amputee person can produce with an accuracy > 95% as well as identifying the movements with the worst performance, which would require further training. This proposed approach is validated with 2 transradial amputees.

关键词： biomechanics biomedical equipment electromyography medical control systems medical signal detection medical signal processing pattern recognition prosthetics sensors

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A Sparse Bayesian Multi-Instance Multi-Label Model for Skin Biopsy Image Analysis

A Sparse Bayesian Multi-Instance Multi-Label Model for Skin ...

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IEEE international conference on bioinformatics and Biomedicine (IEEE BIBM)

作者： Zhang, Gang Su, Xiangyang Huang, Yongjing Lao, Yingrong Liang, Zhaohui Ou, Shanxing Huang, Jimmy Guangzhou Gen Hosp Guangzhou Mil Command Dept Radiol Guangzhou 510010 Guangdong Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China Sun Yat Sen Univ 3rd Affiliated Hosp Dept Dermatol & Venerol Guangzhou 510630 Peoples R China Guangzhou Univ Chinese Med 2nd Affiliated Hosp Guangzhou 510120 Peoples R China Cent China Normal Univ Sch Comp Sci Wuhan Peoples R China York Univ Sch Informat Technol Toronto ON Canada

ISBN: (纸本)9781479913091;9781479913107

As a significant complement for skin surface images, skin biopsy image may reveal causes and severity of many skin diseases, especially in the case of skin cancer inspection. With rapid increment of skin disease patients, computational methods have been introduced for automatic classification of skin images. However, due to the complex relationship among annotation terms and features of local regions, it becomes a great challenge for skin biopsy image feature recognition and annotation. In this paper, we attempt to model the potential knowledge and experience of doctors on skin biopsy image annotation by using a recent proposed machine learning model, named multi-instance multi-label (MIML) model. We show that the relationship among annotation terms and skin biopsy images is naturally consistent with the MIML framework. We further propose a sparse Bayesian MIML algorithm which can produce a probability indicating the confidence of annotating a term. The proposed algorithm framework is evaluated on a real dataset from a large local hospital containing 12,700 skin biopsy images. The results show that the proposed algorithm is effective and prominent.

关键词： skin biopsy image annotation normalized cut s-parse bayesian learning mulit-instance multi-label learning gaussian process

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Face verification using multiple localized face features

Face verification using multiple localized face features

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3rd international Visual Informatics conference, IVIC 2013

作者： Mohd. Zainal, Mohd. Ridzuwary Husain, Hafizah Samad, Salina Abdul Hussain, Aini Universiti Kebangsaan Malaysia Selangor Malaysia

ISBN: (纸本)9783319029573

In this paper, we described face verification execution using different feature extraction methods on different regions of the face. We chose two feature extraction methods which are the Discrete Cosine Transform (DCT) and the Local Binary pattern (LBP). Classification is done separately on for each region using Support Vector Machine. The final verification decision is calculated by combining the classification scores of the face region. The results show that generally, LBP gives better results than DCT on our dataset and parameter settings but both methods did not extract good discriminating features on the nose region. © 2013 Springer international Publishing.

关键词： Local binary pattern

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Human Body Detection in Search and Rescue Operation Conducted by Unmanned Aerial Vehicles

Human Body Detection in Search and Rescue Operation Conducte...

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3rd international conference on Advances in Materials Manufacturing (ICAMMP 2012)

作者： Krerngkamjornkit, Rapee Simic, Milan RMIT Univ Sch Aerosp Mech & Mfg Engn Melbourne Vic Australia

ISBN: (纸本)9783037856482

Human body detection is a fundamental research problem where computer vision could be applied. This research area has wide applications including surveillance, search and rescue missions. Building an effective human body detector framework under wide ranges of weather, lighting and environmental conditions is a challenge task. A variety of sensors and optimisation algorithms are proposed. This paper aims to review the human body detection methodology conducted by the Unmanned Aerial Vehicles (UAV), and the future research for the UAV search and rescue applications.

关键词： Human Body Detection Image Fusion pattern recognition Vision System

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Augmented reality : The future tense of 3D Advertisement

Augmented reality : The future tense of 3D Advertisement

引用

3rd international conference on Computer Communication and Informatics (ICCCI)

作者： Shiva, G. Raajan, N. R. SASTRA Univ Sch Elect & Elect Engn Thanjavur Tamil Nadu India

ISBN: (纸本)9781467329071;9781467329064

We all agree with the fact that the reality is pretty good this will be experience by our sensory organs. Even the virtual world is amazing but the virtual and real world together working is complex. Gratefully this is changing now a days by new tool by which we can see our world with a layer of new information that's we called as Augmented reality (AR). Simply we can say that it's a combination of a virtual object or 3D objects which are overlaid on live camera feed information. We described an integrated solution for advertising different products of same party without using multiple markers. Instead of having multiple markers for augmenting a virtual object we can use single marker for showcasing dissimilar virtual object. The ultimate goal of this paper is to augmenting the virtual video and a 3d object onto a real world on which it will increase the person's conceptual understanding of the subject [1]. For performing this, various methods have been used like model based and feature based methods for making a connection between the 3D object coordinates and the 2D coordinates which are obtained on processing the live camera feed information[14].

关键词： 3D 2D marker Image registration pattern recognition Flash Builder

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Face recognition based on Opposition Particle Swarm Optimization and Support Vector machine

Face Recognition based on Opposition Particle Swarm Optimiza...

引用

3rd IEEE international conference on Signal and Image Processing Applications (ICSIPA)

作者： Hasan, Mohammed Abdullah, Siti Norul Huda Sheikh Othman, Zulaiha Ali Univ Kebangsaan Malaysia Fac Informat Sci & Technol Pattern Recognit Res Grp Bandar Baru Bangi 43600 Malaysia Univ Kebangsaan Malaysia Fac Informat Sci & Technol Data Min & Optimizat Grp Bandar Baru Bangi 43600 Malaysia

ISBN: (纸本)9781479902699;9781479902675

one of the most recently developed face recognition technique has utilized PSO-SVM, this method lacks in the initial phase of the PSO technique. That is in PSO;initially the populations are generated in random manner. Due to this random process, the population results may also be in random. Thus, it is not certain that this method will produce precise result. Hence to avoid this drawback, a modified face recognition method is proposed in this paper. Here, a new face recognition method based on Opposition based PSO with SVM (OPSO-SVM) is introduced. To accomplish the face recognition with our proposed OPSO-SVM, initially feature extraction process is carried out on the image database. In the feature extraction process, the efficient features are extracted and then given to the SVM training and testing process. In OPSO, the populations are generated in two ways: one is random population as same as the normal PSO technique and the other is opposition population, which is based on the random population values. The optimized parameters in SVM by OPSO efficiently perform the face recognition process. Two human face databases FERET and YALE are utilized to analyze the performance of our proposed OPSO-SVM technique and also this OPSO-SVM is compared with PSO-SVM and standard SVM techniques.

关键词： face recognition feature extraction particle swarm optimisation random processes support vector machines

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