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

共 394 条记录，以下是31-40 订阅

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uPAD: Unsupervised Privacy-Aware Anomaly Detection in High Performance computing Systems 8th

uPAD: Unsupervised Privacy-Aware Anomaly Detection in High P...

引用

8th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Ghiasvand, Siavash Tech Univ Dresden Dresden Germany

ISBN: (纸本)9789897583513

Rapid growing complexity of HPC systems in response to demand for higher computing performance, results in higher probability of failures. Early detection of failures significantly reduces the damages caused by failure via impeding their propagation through system. Various anomaly detection mechanism are proposed to detect failures in their early stages. Insufficient amount of failure samples in addition to privacy concerns extremely limits the functionality of available anomaly detection approaches. Advances in machine learning techniques, significantly increased the accuracy of unsupervised anomaly detection methods, addressing the challenge of insufficient failure samples. However, available approaches are either domain specific, inaccurate, or require comprehensive knowledge about the underlying system. Furthermore, processing certain monitoring data such as system logs raises high privacy concerns. In addition, noises in monitoring data severely impact the correctness of data analysis. this work proposes an unsupervised and privacy-aware approach for detecting abnormal behaviors in general HPC systems. Preliminary results indicate high potentials of autoencoders for automatic detection of abnormal behaviors in HPC systems via analyzing anonymized system logs using fast-trainable noise-resistant models.

关键词： pattern Detection Time Series Analysis Anomaly Detection Neural Networks Noise Mitigation

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A Supervised Learning Multiple-F0 Estimation Algorithms for Computer-synthesized Music

A Supervised Learning Multiple-F0 Estimation Algorithms for ...

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8th international conference on computing and Networking Technology (ICCNT)

作者： Guo, Yi Bai, Xinyue Univ Elect Sci & Technol China Coll Automat Chengdu 611731 Peoples R China

ISBN: (纸本)9781467313261

multiple fundamental frequency estimation, or Multiple-F0 estimation, is one of the most important problem on automatic music transcription, but it has not been well resolved up to now. this paper presents a supervised pattern recognition and machine learning methods for computer-synthesized music specifically to Multiple-F0 estimation. Computer-synthesized music is almost free from similar instruments of the differences between different individuals, so it is a good research object. It can be shown in this paper that the experimental results indicate that this method has very good recognition results.

关键词： Automatic music transcription Multiple-F0 estimation PCA pattern recognition

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Emerging Intelligent computing Technology and Applications 2012

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丛书名： Communications in Computer and Information Science

2012年

作者： De-Shuang Huang Phalguni Gupta Xiang Zhang Prashan Premaratne

ISBN: (数字)9783642318375

ISBN: (纸本)9783642318368

this book constitutes the refereed proceedings of the 8th international conference on Intelligent computing, ICIC 2012, held in Huangshan, China, in July 2012. the 242 revised full papers presented in the three volumes LNCS 7389, LNAI 7390, and CCIS 304 were carefully reviewed and selected from 753 submissions. the papers in this volume (CCIS 304) are organized in topical sections on Neural Networks; Particle Swarm Optimization and Niche Technology; Kernel Methods and Supporting Vector Machines; Biology Inspired computing and Optimization; Knowledge Discovery and Data Mining; Intelligent computing in Bioinformatics; Intelligent computing in pattern recognition; Intelligent computing in Image Processing; Intelligent computing in Computer Vision; Intelligent Control and Automation; Knowledge Representation/Reasoning and Expert Systems; Advances in Information Security; Protein and Gene Bioinformatics; Soft computing and Bio-Inspired Techiques in Real-World Applications; Bio-Inspired computing and Applications.

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Human Posture recognition using Artificial Neural Networks 8

Human Posture Recognition using Artificial Neural Networks

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IEEE 8th international Advance computing conference (IACC)

作者： Kale, Hrishikesh Mandke, Prathamesh Mahajan, Hrishikesh Deshpande, Vedant COEP Dept Elect & Telecommun Engn Pune Maharashtra India

ISBN: (纸本)9781538666784

this paper proposes the use of artificial neural networks(ANNs) to classify human postures, using an invasive(intrusive) approach, into 6 categories namely standing, sitting, sleeping and bending - forward and backward. Human posture recognition has numerous applications in the field of healthcare analysis like patient monitoring, lifestyle analysis, elderly care etc. Most importantly, our solution is capable of classifying the aforementioned postures in real-time, by wirelessly(Wi-Fi) acquiring and processing the sensor data on a Raspberry-Pi device with minimal lag. A data-set of 44,800 samples was collected - from 3 subjects - which was used to train and test the neural *** experimenting and testing with a plethora of network architectures, an optimal neural network architecture(6-9-6) with suitable hyper-parameters was determined which gave an overall accuracy of 97.589%.

关键词： pattern-recognition neural-networks posture-recognition wearable-sensors accelerometers embedded systems real time movement classification sensor positioning

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A circular shifting binary descriptor for efficient rotation invariant image matching 26

A circular shifting binary descriptor for efficient rotation...

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26th international conference on pattern recognition / 8th international Workshop on Image Mining - theory and Applications (IMTA)

作者： Soleimani, Parastoo Li, Kin Fun Capson, David W. Univ Victoria Dept Elect & Comp Engn Victoria BC Canada

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Image matching is a key component in computer vision and has many applications. In this work, we propose a circular shifting binary descriptor to increase the speed of rotation invariant image matching algorithms. We can compute the descriptors of the rotated image patches without rotating either the sample points or the image patch by circularly shifting the binary descriptor. thus, operations such as multiplications and divisions from the orientation estimation step are eliminated from the image matching process which significantly reduces the number of operations for computing the descriptor. In addition, our experiments illustrate that the circular shifting binary descriptor shows limited rotation error in comparison with other descriptors such as ORB while attaining comparable mean average precision.

关键词： Computer vision Image matching Estimation Computer architecture Hardware pattern recognition Tuning

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Solving Machine Part Cell Formation Problem Using Genetic Algorithm Based Evolutionary computing 8th

Solving Machine Part Cell Formation Problem Using Genetic Al...

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8th international conference on Soft computing and pattern recognition (SoCPaR) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Sowmiya, N. Valarmathi, B. Gupta, N. Srinivasa VIT Univ Sch Informat Technol & Engn Vellore Tamil Nadu India VIT Univ Sch Informat Technol & Engn Dept Software & Syst Engn Vellore Tamil Nadu India VIT Univ Sch Mech Engn Vellore Tamil Nadu India

ISBN: (纸本)9783319606187;9783319606170

Machine part cell formation is the group technology problem, in which the parts with near similar machining requirements are grouped into part families and the corresponding machines into machine cells. In this paper, a genetic algorithm with a fine tuning procedure is proposed to solve the group technology problem considering only one process plan for each part. the grouping efficacy achieved by the proposed method is comparable to the existing methods in general and better for 11.42% of the datasets.

关键词： Genetic algorithm Clustering Cell formation Cellular manufacturing Grouping efficacy

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Applicability of Soft computing and Optimization Algorithms in Software Testing and Metrics - A Brief Review 8th

Applicability of Soft Computing and Optimization Algorithms ...

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8th international conference on Soft computing and pattern recognition (SoCPaR) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Sharma, Deepak Chandra, Pravin Guru Gobind Singh Indraprastha Univ Univ Sch Informat & Commun Technol Delhi 110078 India

ISBN: (纸本)9783319606187;9783319606170

In spite of many years of work by scientists and specialists on various software qualities, testing stays one of the most broadly honed and concentrated on methodologies for evaluating and improving software quality. Our objective, in this paper, is to present how optimization techniques provide solutions to different and difficult issues in different areas of software engineering. Optimization algorithms are mathematical procedures, which intends to best optimal results for the defect, fault, failure to accomplish tractability, strength, and low arrangement cost. In this paper, a comprehensive overview of software testing and metrics based on soft computing and optimization techniques is presented. In this survey, we try to explain some major problems like defect prediction, software fault prediction and their solutions by soft computing and optimization algorithms. the paper presents an overview of the usage of Mathematical optimization Algorithms and soft computing approaches.

关键词： Optimization algorithms Soft computing Software testing Metrics Software fault prediction

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Person Identification from Full-Body Movement Using String Grammar Fuzzy-Possibilistic C-Medians 8

Person Identification from Full-Body Movement Using String G...

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8th IEEE international conference on Control System, computing and Engineering (ICCSCE)

作者： Chantapakul, Watchanan Auephanwiriyakul, Sansanee theera-Umpon, Nipon Khunlertgit, Navadon Chiang Mai Univ Fac Engn Dept Comp Engn Chiang Mai Thailand Chiang Mai Univ Fac Engn Dept Elect Engn Chiang Mai Thailand Chiang Mai Univ Inst Biomed Engn Chiang Mai Thailand

ISBN: (纸本)9781538663240

Biometrics is a method to identify a person. However, there are several biometric techniques including face recognition, palm recognition, iris recognition, fingerprint recognition, and so on. there is a new approach in biometrics, i.e., identification using full-body movement. In this paper, we introduce a full-body movement in human identification using three Kinects. In particular, we utilize the string grammar fuzzy-possibilistic C-medians (sgFPCNIed) to group string sequences from skeleton frames into pose string, then group the pose string sequences of each person into multi-group to create multi prototypes for each person. the K-nearest neighbor is used to identify the person in the test process on 27 subjects. the system yields 73.33% correct classification on the best validation set of four-fold cross validation.

关键词： person identification syntactic pattern recognition string grammar fuzzy-possibilistic C-medians Kinect

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Automatic Medicinal Plants Classification using Multi-channel Modified Local Gradient pattern with SVM Classifier 8

Automatic Medicinal Plants Classification using Multi-channe...

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Joint 8th international conference on Informatics, Electronics and Vision (ICIEV) / 3rd international conference on Imaging, Vision and pattern recognition (icIVPR) / international conference on Activity and Behavior computing (ABC)

作者： Habiba, Umme Howlader, Md Rasel Islam, Md Aminul Faisal, Rahat Hossain Rahman, Md Mostafijur Univ Barisal Dept Comp Sci & Engn Barisal Bangladesh

ISBN: (纸本)9781728107882

Most of the people in the world rely on traditional medicine which is made from medicinal plants. However, very few works concentrate on automatic classification. therefore, the automatic classification of medicinal plants demands more investigation which is an important issue for conservation, authentication, and production of medicines. In this paper, for automatically classifying medicinal plants, we present a Multi-channel Modified Local Gradient pattern (MCMLGP), a new texture-based feature descriptor that uses different channels of color images for extracting more significant features to improve the performance of classification. We have trained our proposed approach using SVM classifier with various kernels such as linear, polynomial and HI. In addition, we have used different feature descriptors for comparative experimental analysis with MCMLGP by conducting the rigorous experiment on our own medicinal plants dataset. the proposed approach gain higher accuracy (96.11%) than other techniques, and significantly valuable for exploration and evolution of medicinal plants classification.

关键词： Image Classification Medicinal plant LGP Adaptive threshold SVM

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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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