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检索条件"任意字段=6th IAPR International Conference on Pattern Recognition in Bioinformatics"

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Phonetic unification of multiple accents for spanish and arabic languages

Phonetic unification of multiple accents for spanish and ara...

引用

4th Mexican conference on pattern recognition, MCPR 2012

作者： Tanveer, Saad Muhammad, Aslam Martinez-Enriquez, A.M. Escalada-Imaz, G. Department of CS and E U.E.T. Lahore Pakistan Departmeent of CS CINVESTAV-IPN D.F. Mexico Artificial Intelligence Research Institute IIIA-CSIC Spain

ISBN: (纸本)9783642311482

Languages like Spanish and Arabic are spoken over a large geographic area. the people that speak these languages develop differences in accent, annotation and phonetic delivery. this leads to difficulty in standardization of languages for education and communication (both text and oral). the problem is addressed by phonetic dictionaries to some extent. they provide the correct pronunciation for a word. But, they contribute little to standardize or unify the language for a learner. Our system is to provide unification of different accents and dialects. It creates a standard for learning and communication. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： pattern matching

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pattern recognition Techniques Applied to Electric Power Signal Processing

Pattern Recognition Techniques Applied to Electric Power Sig...

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6th international conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

作者： Bousaleh, Ghazi Darwiche, Mohamad Hassoun, Fahed Lebanese Univ Saida Lebanon Eseo Inst Sci & Technol Angers France France Telecom Nantes France

ISBN: (纸本)9781467316583

We propose in this paper an approach whose main objective is to detect disturbances that affect an electric power signal. the method allows us to locate the time occurrence of these disturbances. the signal processing consists of determining two distributions that are based on the energy of the wavelet signal decomposition: the deviation distribution and the deformation distribution. theses distributions are a signature of the disturbance and are able to provide an identification of the type of the problem. the method has been developed using the analysis by the Discrete Wavelet Transform (DWT). the electrical signal is decomposed into several levels by DWT. the different waveforms resolution levels allows us to detect any deviations from the sane signal. the energy distributions data obtained in the first step will be used as feature vectors for training an artificial neural network (ANN) with multilayer perceptrons (MLPs) and support vector machines (SVMs) to classify the Power Quality Disturbance (PQD).

关键词： multilayer perceptrons pattern recognition power engineering computing power supply quality signal resolution support vector machines wavelet transforms

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Run-time composite event recognition 12

Run-time composite event recognition

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6th ACM international conference on Distributed Event-Based Systems, DEBS'12

作者： Artikis, Alexander Sergot, Marek Paliouras, Georgios Demokritos Athens 15310 Greece Department of Computing Imperial College London United Kingdom

ISBN: (纸本)9781450313155

Events are particularly important pieces of knowledge, as they represent activities of special significance within an organisation: the automated recognition of events is of utmost importance. We present RTEC, an Event Calculus dialect for run-time event recognition and its Prolog implementation. RTEC includes a number of novel techniques allowing for efficient run-time recognition, scalable to large data streams. It can be used in applications where data might arrive with a delay from, or might be revised by, the underlying event sources. We evaluate RTEC using a real-world application. Copyright © 2012 ACM.

关键词： pattern matching

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Classification Model of Seed Cotton Grade Based on Least Square Support Vector Machine Regression Method

Classification Model of Seed Cotton Grade Based on Least Squ...

引用

IEEE 6th international conference on Information and Automation for Sustainability (ICIAFS)

作者： Si Chen Ling Li-na Yuan Rong-chang Sun Long-qing SUNY Buffalo Dept Elect Engn Buffalo NY 14260 USA China Agr Univ Beijing Peoples R China Power Automat Dept Beijing Peoples R China

ISBN: (纸本)9781467319751;9781467319768

Grade classification of seed cotton is a major problem that has an significant impact on the agricultural economy. According to characteristics like impurities, yellowness and brightness that extract from images of seed cotton, constructing classification model of seed cotton base on the least square method. Using support vector machine regression to come up with a well improved algorithm. After full learning, seed cotton classification accuracy satisfy the actual application needs.

关键词： seed cotton fuzzy math pattern recognition least square method support vector machine

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Multiple feature selectoin for pattern recognition using ID3 ensemble system

Multiple feature selectoin for pattern recognition using ID3...

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6th international conference on Genetic and Evolutionary Computing (ICGEC)

作者： Nakatsu, Koichiro Furuta, Hitoshi Takahashi, Kyousuke Ishibashi, Ken Yasuda, Shigeki Osaka Jonan Womens Jr Coll Sumiyoshi Ku Higashi Osaka Japan Kansai Univ Takatsuki Osaka Japan

ISBN: (纸本)9780769547633;9781467321389

In pattern recognition, feature selection is a quite important process for constructing practical systems. However, because there are many features as candidates to recognize object, it is difficult to select appropriate features for pattern recognition systematically. the previous research proposed a pattern recognition method using the ensemble system based on fuzzy classifier for multiple feature selection. However, this method can not apply for the problems with many input vectors because it takes a lot of time for learning when the number of the input vector increases. In this study, an attempt is made to overcome the problem by introducing ID3 (Iterative Dichotomizer 3) with classifiers consisting of many feature vectors. ID3 constructs a decision tree for multiple feature selection with the results obtained from classifiers based on each feature. therefore, it is possible to select appropriate features applied many input vectors. Several benchmark problems are presented to demonstrate the efficiency and applicability of the proposed method.

关键词： pattern recognition machine learning feature selection ID3

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Test System for Defect Detection in Construction Materials with Ultrasonic Waves by Support Vector Machine and Neural Network

Test System for Defect Detection in Construction Materials w...

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6th international conference on Soft Computing and Intelligent Systems (SCIS) / 13th international Symposium on Advanced Intelligence Systems (ISIS)

作者： Saechai, Saowanee Kongprawechnon, Waree Sahamitmongkol, Raktipong Thammasat Univ Sirindhorn Int Inst Technol Sch Informat Comp & Commun Technol Pathum Thani Thailand Thammasat Univ Sirindhorn Int Inst Technol Construct & Maintenance Technol Res Ctr Pathum Thani Thailand

ISBN: (纸本)9781467327435;9781467327428

this paper introduces a newly developed test system for structure inspection and evaluation of cement-based products by applying ultrasonic test with support vector machine (SVM) classifier. In other words, this paper represents a novel method based on SVM for defect detection, classification of number of defects, and identification of defect materials. With the system, pattern of ultrasonic waves for each case of specimen can be obtained from direct and indirect measurements. Machine learning algorithm called support vector machine and artificial neural network (ANN) are employed for classification and verification of the wave patterns obtained from different samples. By applying the system, the presence or absence of a defect in mortar can be identified. Moreover, the system can also classify the number of defects and identify the defect materials being inside the mortar. For classification, input features are extracted in different ways and the numbers of training sets are varied. Base on the results from SVM, the signals extracted in frequency domain gives better performance than time domain. Using a larger training set can give more satisfactory results. In this article, the methodology is explained and the classification results are discussed. the effectiveness of the developed test system is evaluated. Comparison of the classification results that obtained by between SVM and ANN classifiers is also demonstrated. this study shows that this technique based on pattern recognition has a high potential for practical inspection of concrete structure.

关键词： ultrasonic pulse velocity defect detection pattern recognition support vector machine neural network

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Mathematical Methodologies in pattern recognition and Machine Learning: Contributions from the international conference on pattern recognition

引用

2012年

作者： Pedro Latorre Carmona J Salvador Snchez Ana Luisa N Fred

ISBN: (纸本)9781461450757

this volume features key contributions from the international conference on pattern recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012. the conference provided a major point of collaboration between researchers, engineers and practitioners in the areas of pattern recognition, both from theoretical and applied perspectives, with a focus on mathematical methodologies. Contributions describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, and experimental and theoretical studies which yield new insights that provide key advances in the field. this book will be suitable for scientists and researchers in optimization, numerical methods, computer science, statistics andfor differential geometers and mathematical physicists.

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Automatic design of artificial neural networks and associative memories for pattern classification and pattern restoration

Automatic design of artificial neural networks and associati...

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4th Mexican conference on pattern recognition, MCPR 2012

作者： Sossa, Humberto Garro, Beatriz A. Villegas, Juan Avilés, Carlos Olague, Gustavo CIC-IPN Juan de Dios Batiz S/N Col. Nva. Industrial Vallejo México D. F. Mexico UAM-Azcapotzalco Av. San Pablo Xalpa 180. Azcapotzalco México D. F. Mexico CICESE Carretera Ensenada-Tijuana 3918 Zona Playitas Ensenada B. C. Mexico

ISBN: (纸本)9783642311482

In this note we present our most recent advances in the automatic design of artificial neural networks (ANNs) and associative memories (AMs) for pattern classification and pattern recall. Particle Swarm Optimization (PSO), Differential Evolution (DE), and Artificial Bee Colony (ABC) algorithms are used for ANNs;Genetic Programming is adopted for AMs. the derived ANNs and AMs are tested with several examples of well-known databases. As we will show, results are very promising. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Neural networks

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Monitoring and control of machining process by data mining and pattern recognition

Monitoring and control of machining process by data mining a...

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2012 6th international conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2012

作者： Yacout, Soumaya Meshreki, Mouhab Attia, Helmi Department of Mathematics and Industrial Engineering École Polytechnique Succ. Centre-ville Montréal QC H3C3A7 Canada Aerospace Manufacturing Technology Centre National Research Council Canada 5145 Decelles avenue Montreal QC H3T2B2 Canada

ISBN: (纸本)9780769546872

In this paper we present a novel approach to the problem of understanding, monitoring, and controlling the machining process of composites materials. the approach is called Logical Analysis of Data (LAD). It is based on data mining and pattern recognition, and uses a machine learning artificial intelligence technique. this novel approach is used for the first time in order to define machining conditions that lead to conforming products, and also conditions which will lead to nonconforming products. In this paper, we introduce the LAD technique, we apply it to the machining of composites, and we report on the results based on data obtained experimentally. We conclude with a discussion of the potential use of LAD in manufacturing. © 2012 Crown Copyright.

关键词： Data mining

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Image and Signal Processing - 5th international conference, ICISP 2012, Proceedings

Image and Signal Processing - 5th International Conference, ...

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5th international conference on Image and Signal Processing, ICISP 2012

ISBN: (纸本)9783642312533

the proceedings contain 67 papers. the topics discussed include: Bayesian image matting using infrared and color cues;salient pixels and dimensionality reduction for display of multi/hyperspectral images;SVM and haralick features for classification of high resolution satellite images from urban areas;multi-model approach for multicomponent texture classification;simultaneous multispectral imaging and illuminant estimation using a stereo camera;kernel-based Laplacian smoothing method for 3D mesh denoising;embedded real-time video processing system on FPGA;edge preserving image fusion based on contourlet transform;selecting vision operators and fixing their optimal parameters values using reinforcement learning;a phase congruency based document binarization;methodology for acoustic characterization of a labial constraint in speech production;and nonlinear blind source separation applied to a simple bijective model.

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