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检索条件"任意字段=International Workshop on Intelligent Computer in Pattern Analysis/Synthesis"

共 294 条记录，以下是61-70 订阅

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Cancelable biometrics for finger vein recognition

Cancelable biometrics for finger vein recognition

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international workshop on Sensing, Processing and Learning for intelligent Machines (SPLINE)

作者： Emanuela Piciucco Emanuele Maiorana Christof Kauba Andreas Uhl Patrizio Campisi Section of Applied Electronics Roma Tre University Roma Italy Department of Computer Sciences Salzburg University Salzburg Austria

ISBN: (纸本)9781467389181

Cancelable biometrics is one of the possible solutions to security and privacy problems in biometrics-based recognition systems. In this paper we propose the use of two classical transformations, block re-mapping and image warping, for the definition of cancelable biometrics from finger vein pattern images. Specifically, the impact on matching performance of the employed distortions, as well as the effects of their parameters' selection, are here investigated. An analysis of the renewability of the employed approaches is also provided. Performance comparable with what achieved in the unprotected approach can be reached in case of block re-mapping transformation, which is also able to provide renewability.

关键词： Biometrics (access control) Veins Security Privacy Feature extraction Distortion Databases

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Towards Assessing the Technical Debt of Undesired Software Behaviors in Design patterns

Towards Assessing the Technical Debt of Undesired Software B...

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international workshop on Managing Technical Debt (MTD)

作者： Derek Reimanis Clemente Izurieta Computer Science Department Montana State University Bozeman Montana USA

ISBN: (纸本)9781509038558

Providing software developers and researchers with useful technical debt analysis tools is an instrumental outcome of software engineering and technical debt research. Such tools aggregate industry best practices to provide users with organized and quantifiable metrics that can help minimize the time it takes to synthesize and make an intelligent future decision regarding a system. Today, most tools rely primarily on structural measurements from static analysis to generate results. However, it is also necessary to consider measurements that capture the behavior of software, as these represent additional complexities within a system that structural measurements are incapable of detecting. Herein, we present our position, that more effort needs to be placed towards understanding software behavior so that technical debt analysis tools can begin supporting them, in order to provide tool users with a more accurate and complete view of their system. In this paper, we describe this problem in the context of design patterns and outline an effective method to talk about behaviors in the future. We create and classify two example behaviors using our method, both of which increase the technical debt in their respective design pattern applications.

关键词： IP networks Observers Runtime Software systems Software measurement

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Using a Novel LDA-Ensemble Framework to Classification of Motor Imagery Tasks for Brain-computer Interface Applications

Using a Novel LDA-Ensemble Framework to Classification of Mo...

引用

workshop on computer Architecture, Embedded Systems, SoC, and VLSI/EDA / international computer Symposium (ICS)

作者： Chiu, Ching-Yu Chen, Chih-Yu Lin, Yang-Yin Chen, Shi-An Lin, Chin-Teng Natl Chiao Tung Univ Coll Photon Hsinchu Taiwan Natl Chiao Tung Univ Inst Biomed Engn Hsinchu Taiwan Natl Chiao Tung Univ Brain Res Ctr Hsinchu Taiwan

ISBN: (纸本)9781614994848;9781614994831

In this paper, we introduce a novel linear discriminate analysis (LDA) ensemble classifier utilizing the Mindo as a brain-computer interface (BCI) device to deal with the problem of motor imagery classification. With regard to the composition of the proposed system, we combine filter bank, sub-band common spatial pattern (SBCSP), LDA together for extracting features of EEG data and classifying the motor imagery with left or right states. In addition, we also employ a gradient descent (GD) algorithm to find the best weight associated with probability fusion function. This novel architecture not only boosts the accuracy of classification but maintains the computational efficiency of the system. Therefore, the proposed LDA-ensemble framework is able to be satisfied with each subject as demonstrated in Section III.

关键词： brain-computer interface (BCI) motor imagery classification linear discriminate analysis (LDA)

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An Obstruction-Check Approach to Mining Closed Sequential patterns in Data Streams

An Obstruction-Check Approach to Mining Closed Sequential Pa...

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workshop on computer Architecture, Embedded Systems, SoC, and VLSI/EDA / international computer Symposium (ICS)

作者： Chang, Ye-In Li, Chia-En Chin, Tzu-Lin Natl Sun Yat Sen Univ Dept Comp Sci & Engn Kaohsiung Taiwan

ISBN: (纸本)9781614994848;9781614994831

Online mining sequential patterns over data streams is an important problem in data mining. There are many applications of using sequential patterns in data streams, such as market analysis, network security and web tracking. For solving the problem of data mining in the time-based sliding window, Chang et al. proposed an algorithm called SeqStream. The SeqStream algorithm still scans the sliding window many times when IST(Inverse Closed Sequence Tree) needs to be updated. In this paper, we propose an obstruction-check approach to maintain the result of closed sequential patterns. Our approach is designed based on the lattice structure. Based on the lattice structure, we propose the EULB (Exact Update based on Lattice structure with Bit stream)-Lattice algorithm that is an exact method for mining data streams. We record additional information, instead of scanning the entire sliding window. The simulation results show that the proposed algorithm outperforms the SeqStream algorithm.

关键词： closed sequential pattern data stream lattice sequential pattern sliding window

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1st international Conference on intelligent Computing, Communication and Devices, ICCD 2014

1st International Conference on Intelligent Computing, Commu...

引用

1st international Conference on intelligent Computing, Communication and Devices, ICCD 2014

ISBN: (纸本)9788132220084

The proceedings contain 59 papers. The special focus in this conference is on intelligent Computing, Communication and Devices. The topics include: A survey of security concerns in various data aggregation techniques in wireless sensor networks;frequency domain incremental strategies over distributed network;a probabilistic packet filtering-based approach for distributed denial of service attack in wireless sensor network;location-based coordinated routing protocol for wireless sensor and actor networks;energy saving performance analysis of hierarchical data aggregation protocols used in wireless sensor network;a distributed secured localization scheme for wireless sensor networks;relating perceptual feature space and context drift information in query by humming system;first-fit semi-partitioned scheduling based on rate monotonic algorithm;a comparative study of correlation based stereo matching algorithms;a novel approach for jamming and tracking of mobile objects;grid computing-based performance analysis of power system;hybrid edge detection-based image steganography technique for color images;biomedical image registration using genetic algorithm;unsupervised segmentation of satellite images based on neural network and genetic algorithm;an intelligent method for moving object detection;a decision-driven computer forensic classification using ID3 algorithm;detection of video objects in dynamic scene using local binary pattern subtraction method;static hand gesture recognition based on fusion of moments;development of Odia language corpus from modern news paper texts and a rule-based concatenative approach to speech synthesis in Indian language text-to-speech systems.

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Guiding intelligent testbench automation using data mining and formal methods

Guiding intelligent testbench automation using data mining a...

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international Design and Test workshop

作者： Eman El Mandouh Amr G. Wassal Mentor Graphics Corporation Computer Engineering Department Cairo University Egypt

Achieving coverage closure is consistently identified as one of the most difficult challenges during the functional verification of today's HW designs. Constraint random testing as well as coverage directed test generation (CDTG) techniques have been proposed previously with different degree of success. This paper presents a framework for speeding up the coverage closure of the design under verifications (DUV) using state of the art verification techniques. The framework starts with random simulation of the DUV followed by frequent pattern mining of simulation data to extract some valid design constraints. Simulation coverage database is analyzed and the coverage holes are identified and directed to the formal verification step, formal analysis is used to prove the unreachability of some coverage holes during simulation run. Formally proven unreachable cover items as well as automatically extracted design constraints are then fed as test template specification to direct the intelligent testbench generation to rapidly achieve the coverage of previously uncovered corner cases. Our experimental results demonstrate the effectiveness of the proposed approach in closing the coverage loop for a set of today's RTL designs.

关键词： Data mining Data models Analytical models Formal verification Algorithm design and analysis Automation Databases

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Real time object tracking via a mixture model

Real time object tracking via a mixture model

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IEEE international workshop on Robot and Human Communication (ROMAN)

作者： Dongxu Gao Zhaojie Ju Jiangtao Cao Honghai Liu Intelligent Systems and Biomedical Robotics group School of Computing’ University of Portsmouth Portsmouth England Department of Information and Control Engineering Liaoning Shihua University Fushun Liaoning China

Object tracking has been applied in many fields such as intelligent surveillance and computer vision. Although much progress has been made, there are still many puzzles which pose a huge challenge to object tracking. Currently, the problems are mainly caused by appearance model as well as real-time performance. A novel method was been proposed in this paper to handle both of these problems. Locally dense contexts feature and image information (i.e. the relationship between the object and its surrounding regions) are combined in a Bayes framework. Then the tracking problem can be seen as a prediction question which need to compute the posterior probability. Both scale variations and temple updating are considered in the proposed algorithm to assure the effectiveness. To make the algorithm runs in a real time system, a Fourier Transform (FT) is used when solving the Bayes equation. Therefore, the MMOT (Mixture model for object tracking) runs in real-time and performs better than state-of-the-art algorithms on some challenging image sequences in terms of accuracy, quickness and robustness.

关键词： Computational modeling Image color analysis Hidden Markov models computer vision Object tracking pattern recognition Real-time systems

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6th IAPR TC3 international workshop on Artificial Neural Networks for pattern Recognition, ANNPR 2014

引用

6th IAPR TC3 international workshop on Artificial Neural Networks for pattern Recognition, ANNPR 2014

ISBN: (纸本)9783319116556

The proceedings contain 27 papers. The special focus in this conference is on Artificial Neural Networks for pattern Recognition. The topics include: Large margin distribution learning;a decorrelation approach for pruning of multilayer perceptron networks;unsupervised active learning of CRF model for cross-lingual named entity recognition;incremental feature selection by block addition and block deletion using least squares SVRs;low-dimensional data representation in data analysis;analyzing dynamic ensemble selection techniques using dissimilarity analysis;hidden Markov models based on generalized Dirichlet mixtures for proportional data modeling;majority-class aware support vector domain oversampling for imbalanced classification problems;forward and backward forecasting ensembles for the estimation of time series missing data;dynamic weighted fusion of adaptive classifier ensembles based on changing data streams;combining bipartite graph matching and beam search for graph edit distance approximation;computing upper and lower bounds of graph edit distance in cubic time;a new multi-class fuzzy support vector machine algorithm;a reinforcement learning algorithm to train a Tetris playing agent;automatic bridge crack detection - a texture analysis-based approach;part-based high accuracy recognition of serial numbers in bank notes;comparative study of feature selection for white blood cell differential counts in low resolution images;end-shape recognition for Arabic handwritten text segmentation;intelligent ensemble systems for modeling NASDAQ microstructure;face recognition based on discriminative dictionary with multilevel feature fusion;investigating of preprocessing techniques and novel features in recognition of handwritten Arabic characters and a time series classification approach for motion analysis using ensembles in ubiquitous healthcare systems.

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3rd international Conference on Frontiers in intelligent Computing: Theory and Applications, FICTA-2014

3rd International Conference on Frontiers in Intelligent Com...

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3rd international Conference on Frontiers in intelligent Computing: Theory and Applications, FICTA-2014

ISBN: (纸本)9783319119328

The proceedings contain 95 papers. The special focus in this conference is on Data Warehousing and Mining, Machine Learning, Mobile and Ubiquitous Computing, AI, E-commerce and Distributed Computing and Soft Computing, Evolutionary Computing, Bio-inspired Computing and *** topics include: Approximation neural network for phoneme synthesis;pattern-matching for speaker verification;online clustering algorithm for restructuring user web search results;optimal computer based analysis for detecting malarial parasites;a survey of dynamic program analysis techniques and tools;extended self organizing map with probabilistic neural network for pattern classification problems;fuzzy rule-based adaptive proportional derivative controller;sentence completion using text prediction systems;architectural recommendations in building a network based secure, scalable and interoperable internet of things middleware;mean interleaved round robin algorithm;cryptanalysis of image encryption based on permutation-substitution using chaotic map and Latin square image cipher;windowed Huffman coding with limited distinct symbols by least recently used symbol removable;theme interception sequence learning;energy efficient distributed topology control technique with edge pruning;dynamic cache resizing in flashcache;heuristic for context detection in time varying domains;construction of automated concept map of learning using hashing technique;analysis of estimation techniques for feature based navigation of unmanned air vehicles;curved videotext detection and extraction;an approach to utilize FMEA for autonomous vehicles to forecast decision outcome;diffusion and encryption of digital image using genetic algorithm;character recognition using teaching learning based optimization;the fuzzy robust graph coloring problem;detection of moving object and image steganography using integer wavelet transform based on color space approach.

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Keynote Speech:intelligent pattern Recognition and Forensics——Modeling and Simulation in HC Interactive Learning Environment

Keynote Speech:Intelligent Pattern Recognition and Forensics...

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2012 2nd international Conference on Social Sciences and Society(ICSSS 2012)

作者： Patrick S.P.Wang Computer and Information Science Northeastern University

This talk deals with fundamental aspects of Grammatical Semantics, Ambiguity, intelligent pattern Recognition (IPR) and applications. It basically includes the following: Overview of 3D Biometric Technology and Applications, Importance of Security: A Scenario of Terrorists Attack,, What are Biometric Technologies? Biometrics: analysis vs synthesis, analysis: Concept of Syntax. Semantics, Ambiguity and Interactive pattern Recognition, Importance of Measurement, How it works: Fingerprint Extraction and Matching, Iris, and Facial analysis, Authentication Applications, Thermal Imaging: Emotion Recognition. synthesis in Biometrics, Modeling and Simulation, and more Examples and Applications of 3D Biomedical Imaging in Interactive Web/Video Networking Fuzzy Learning Environment. Finally, some future research directions are discussed.

关键词： Keynote Speech:intelligent pattern Recognition and Forensics Modeling and Simulation in HC Interactive Learning Environment Simulation

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