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检索条件"任意字段=8th International Conference on Computing and Pattern Recognition, ICCPR 2019"

共 395 条记录，以下是251-260 订阅

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Development and Application of SF6 Insulated GIS True Defect Simulation Device

Development and Application of SF6 Insulated GIS True Defect...

引用

international conference on Renewable Power Generation

作者： Zhang Shiling State Grid Chongqing Electric Power Company Chongqing Electric Power Research Institute Chongqing 401123

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

GIS equipment has the advantages of compact structure and high reliability, but in recent years, the operation data show that GIS equipment causes insulation accident due to the insulation defects during the manufacture and operation, it is urgent to quantitatively analyze the operating parameters and state characteristics of GIS equipment under the condition of insulation defects. therefore, the GIS real defect simulator has been designed and developed. the device consists of four parts: the sulfur fluoride gas chamber, solid insulation parts, the defect simulation device, observation and measurement device four parts. the defect device can effectively simulate four typical insulation defects of free metal particles, bubble defects in the solid insulation, needle/plate and plate/plate electrode discharge, and apply two types of DC/AC voltage. three-dimensional finite element simulation model of GIS true type defect simulation device is first set up in this paper. the electric field distribution of four typical insulation defects, the central guide rods and the basin insulators in the simulation device is analyzed, and reasons for decomposition of the SF6 gas body under the defect condition are analyzed theoretically. On this basis, the variation trend of SF6's trace gas with time, the characteristics of fully mechanized partial discharge and the trend of gas change under the condition of failure are analyzed. the defect type clustering algorithm is proposed and applied to pattern recognition of fault types of actual gas combiner. the research results have the theoretical guiding value for the fault diagnosis and pattern recognition of GIS equipment.

关键词： SF6 gas insulated AC GIS Defect simulation device Finite element method pattern recognition

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Intelligent Decision Technologies 2016: Proceedings of the 8th KES international conference on Intelligent Decision Technologies (KES-IDT 2016) Part II

引用

2018年

作者： Ireneusz Czarnowski Alfonso Mateos Caballero Robert J Howlett Lakhmi C Jain

ISBN: (纸本)9783319819266

the KES-IDT-2016 proceedings give an excellent insight into recent research, both theoretical and applied, in the field of intelligent decision making. the range of topics explored is wide, and covers methods of grouping, classification, prediction, decision support, modelling and many more in such areas as finance, linguistics, medicine, management and transportation. this proceedings contain several sections devoted to specific topics, such as: Specialized Decision Techniques for Data Mining, Transportation and Project Management pattern recognition for Decision Making Systems New Advances of Soft computing in Industrial and Management Engineering Recent Advances in Fuzzy Systems Intelligent Data Analysis and Applications Reasoning-based Intelligent Systems Intelligent Methods for Eye Movement Data Processing and Analysis Intelligent Decision Technologies for Water Resources Management Intelligent Decision Making for Uncertain Unstructured Big Data Decision Making theory for Economics Interdisciplinary Approaches in Business Intelligence Research and Practice pattern recognition in Audio and Speech Processing the KES-IDT conference is a well-established international annual conference, interdisciplinary in nature. these two volumes of proceedings form an excellent account of the latest results and outcomes of recent research in this leading-edge area.

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Intelligent Decision Technologies 2016: Proceedings of the 8th KES international conference on Intelligent Decision Technologies (KES-IDT 2016) Part I

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2018年

作者： Ireneusz Czarnowski Alfonso Mateos Caballero Robert J Howlett Lakhmi C Jain

ISBN: (纸本)9783319819273

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Searching a pattern in Token Scene Image via Multi-Variant Symmetric pattern Matching Technique 8

Searching a Pattern in Token Scene Image via Multi-Variant S...

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8th international conference on computing, Communication and Networking Technologies (ICCCNT)

作者： Dev, Deep Suman Kisku, Dakshina Ranjan Neotia Inst Technol Management & Sci Dept Informat Technol DH RdSouth 24 Pgs Kolkata 743368 India Natl Inst Technol Durgapur Dept Comp Sci & Engn Burdwan 713209 W Bengal India

ISBN: (纸本)9781509030385

One of the fundamental tasks of pattern recognition is pattern matching. It is the act of checking for presence of a pattern's constituents within token image to have exact match. For that, most distinctive fiducial features of pattern have to be assessed and searched in the sliding windows of same pattern size formed by logically dividing the token scene image. As huge numbers of sliding windows are to be checked with pattern, pattern matching process should be time efficient and to increase pattern matching accuracy impacts due to illumination, resolution, occlusion and pose variation must be reduced. For pattern matching, this paper presents a novel local feature descriptor, multi variant symmetric local graph structure (MVSLGS) taking into account symmetric local graph structure (SLGS) as precedent approach. the computational adequacy of the proposed approach is tested on two publicly available databases with high matching accuracy, showing its proficiency over the process of pattern matching.

关键词： pattern matching local feature descriptor Symmetric LGS

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Cogno-Detective System for Body Odor Sensing 8

Cogno-Detective System for Body Odor Sensing

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8th IEEE international conference on Computational Intelligence and computing Research (IEEE ICCIC)

作者： Kanakam, Prathyusha Hussain, S. Mahaboob Chakravarthy, A. S. N. MVGR Coll Engn Autonomous Dept Comp Sci & Engn Vizianagaram India Vishnu Inst Technol Dept Comp Sci & Engn Bhimavaram India JNTU Kakinada UCEV Dept Comp Sci & Engn Kakinada India

ISBN: (纸本)9781509066216

the Modern decade of future Internet stepping into all the technologies includes sensors, artificial intelligence, pattern recognition and machine learning. As sensor technology increases its liabilities by extending to novel recognition methods for identifying an individual. Smell print is a state-of-art technique to perform authentication, verification and validation of a person to apply in fields of human tracking, criminal investigation and canine training etc. this paper describes the compounds combination of human odor, the factors that influence the human odor and sources of smell print in a human body. It gives a prototype for Cogno-detective system for the human odor in order to imitate the human olfaction and procedure to implement the artificial olfaction mechanism.

关键词： sensors volatile organic compounds(VOCs) pattern recognition machine learning artificial intelligence cogno-detective system

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A new predictive approach to variables selection through Genetic Algorithm and Fuzzy Adaptive Resonance theory Using medical diagnosis as a case 8

A new predictive approach to variables selection through Gen...

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8th international conference on Ambient Systems, Networks and Technologies (ANT) / 7th international conference on Sustainable Energy Information Technology (SEIT)

作者： Djellali, Choukri Adda, Mehdi Univ Quebec Math Comp Sci & Engn Dept 300 Allee Ursulines Rimouski PQ G5L 3A1 Canada

Variables selection is challenging task due mainly to huge search space. this study addresses the increasingly encountered challenge of variables selection. It addresses the application of machine learning techniques to the problem of variables selection. We detailed the various models of the variables selection and examined the basic steps that are used to select the cost-effective predictors. We also walked through the initial settings and all variables selection stages, including architecture configuration, strategy generation, learning, model induction, and scoring. Results from this study show that the cost and generalization were seen to improve significantly in terms of computing time and recognition accuracy when the proposed system is applied for medical diagnosis. Good comparisons with an experimental study demonstrate the multidisciplinary applications of our approach. 1877-0509 (C) 2017 the Authors. Published by Elsevier B.V.

关键词： Data Mining pattern recognition Machine Learning Clustering Variables Selection Genetic Algorithm

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Multiclass AdaBoost Classifier Parameter Adaptation for pattern recognition 8th

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8th international conference on Image Processing and Communications (IP&C)

作者： Dembski, Jerzy Gdansk Univ Technol Fac Elect Telecommun & Informat Ul Narutowicza 11-12 PL-80952 Gdansk Poland

ISBN: (纸本)9783319472744;9783319472737

the article presents the problem of parameter value selection of the multiclass "one against all" approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary two-class classifiers in recognition problems. In this paper an original method of selecting the parameter values of the assembling algorithm using many similar face recognition tasks is proposed. the parameter optimization is done by checking all possible vectors of parameter values. the recognition results with optimized parameter values is 10% better in 8-class face database famous48 (http://***. pl/documents/176468/27493127/***) tasks than using random heuristic which can be represented by the average of all possible vectors of parameter values.

关键词： Face recognition Multiclass AdaBoost classifier Haar features

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Identifying Smartphone Users based on their Activity patterns via Mobile Sensing 8

Identifying Smartphone Users based on their Activity Pattern...

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8th international conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN) / 7th international conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICth)

作者： Ehatisham-ul-Haq, M. Azam, Muhammad Awais Naeem, Usman Rehman, Shafiq Ur Khalid, Asra Univ Engn & Technol Fac Telecom & Informat Engn Taxila Punjab Pakistan Univ East London Sch Architecture Comp & Engn London E16 2RD England Umea Univ Dept Appl Phys & Elect SE-90187 Umea Sweden COMSATS Inst Informat Technol Dept Comp Sci Wah Campus Islamabad Pakistan

Smartphones are ubiquitous devices that enable users to perform many of their routine tasks anytime and anywhere. With the advancement in information technology, smartphones are now equipped with sensing and networking capabilities that provide context-awareness for a wide range of applications. Due to ease of use and access, many users are using smartphones to store their private data, such as personal identifiers and bank account details. this type of sensitive data can be vulnerable if the device gets lost or stolen. the existing methods for securing mobile devices, including passwords, PINs and pattern locks are susceptible to many bouts such as smudge attacks. this paper proposes a novel framework to protect sensitive data on smartphones by identifying smartphone users based on their behavioral traits using smartphone embedded sensors. A series of experiments have been conducted for validating the proposed framework, which demonstrate its effectiveness. (c) 2017 the Authors. Published by Elsevier B.V.

关键词： Activity recognition Behavioral Biometrics Continuous Sensing Mobile Device Security Data Privacy Mobile Sensing Ubiquitous computing User Identification

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Using PEGs for automatic extraction of memory access descriptions to support data-parallel pattern recognition 17

Using PEGs for automatic extraction of memory access descrip...

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8th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 6th Workshop on Design Tools and Architectures For Multicore Embedded computing Platforms, PARMA-DITAM 2017

作者： Auras-Rodríguez, María H. Zimmermann, Anthony Ascheid, Gerd Leupers, Rainer Institute for Communication Technologies and Embedded Systems RWTH Aachen University Aachen52056 Germany

ISBN: (纸本)9781450348775

In this paper, we present a novel approach that assists in the task of data-parallel pattern recognition. the classification of program code into parallel patterns relies mainly in the extraction of characteristics that describe memory access operations. Our tool automatically generates static decidable memory access characterizations using a Program Expression Graph (PEG) representation of input programs. We analyze the main properties of PEGs that favor the corresponding extraction algorithm in comparison to other input representations. Additionally, we demonstrate the effectiveness of our proposed method using the PolyBench kernels for the recognition of the data-parallel patterns that drive the Bones skeleton-based parallellizing compiler, targeting as case study modern embedded platforms (i.e. Keystone II and Parallella Board). © 2017 ACM.

关键词： Extraction

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

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ISBN: (纸本)9781450348775

the proceedings contain 6 papers. the topics discussed include: dataflow acceleration of Scikit-learn Gaussian process regression;VectorPU: a generic and efficient data-container and component model for transparent data transfer on GPU-based heterogeneous systems;using PEGs for automatic extraction of memory access descriptions to support data-parallel pattern recognition;on boosting energy-efficiency of heterogeneous embedded systems via game theory;scaling binarized neural networks on reconfigurable logic;MTP-Caffe: memory, timing, and power aware tool for mapping CNNs to GPUs.

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