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检索条件"任意字段=5th International Workshop on Graph-Based Representations in Pattern Recognition"

共 194 条记录，以下是91-100 订阅

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Joint IAPR international workshops on Structural and Syntactic pattern recognition and Statistical Techniques in pattern recognition, SSPR and SPR 1998.

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7th Joint IAPR international workshop on Structural and Syntactic pattern recognition, SSPR 1998 and 2nd international workshop on Statistical Techniques in pattern recognition, SPR 1998

ISBN: (纸本)3540648585

the proceedings contain 113 papers. the special focus in this conference is on Structural Matching, Grammatical Inference and recognition of 2D and 3D Objects. the topics include: Error-tolerant graph matching;semantic content based image retrieval using object-process diagrams;pattern recognition methods in image and video databases;efficient matching with invariant local descriptors;integrating numerical and syntactic learning models for pattern recognition;synthesis of function-described graphs;marked subgraph isomorphism of ordered graphs;distance evaluation in pattern matching based on frontier topological graph;syntactic interpolation of fractal sequences;minimizing the topological structure of line images;genetic algorithms for structural editing;the noisy subsequence tree recognition problem;object recognition from large structural libraries;acquisition of 2-d shape models from scenes with overlapping objects using string matching;a taxonomy of occlusion in view signature ii representations;a survey of non-thinning based vectorization methods;a benchmark for raster to vector conversion systems;network-based recognition of architectural symbols;recovering image structure by model-based interaction map;an improved scheme to fingerprint classification;character recognition with k-head finite array automata;using semantics in matching cursive chinese handwritten annotations;concavity detection using a binary mask-based approach;structural indexing of line pictures with feature generation models;nonlinear covariance for multi-band image data;a neural network for image smoothing and segmentation;prototyping structural descriptions and neural network based learning of local compatibilities for segment grouping.

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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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Possibilistic clustering approach to trackless ring pattern recognition in RICH counters

Possibilistic clustering approach to trackless ring Pattern ...

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5th international workshop on Fuzzy Logic and Applications

作者： Massone, AM Studer, L Masulli, F Univ Pisa Dipartimento Informat I-56127 Pisa Italy CNR INFM LAMIA I-16146 Genoa Italy Univ Lausanne IPHE CH-1015 Lausanne Switzerland

the pattern recognition problem in Ring Imaging CHerenkov (RICH) Counters concerns the identification of art unknown number of rings whose centers and radii are assumed to be unknown. In this paper we present art algorithm based oil the possibilistic approach to Clustering that automatically finds both the number of rings and their position without any a priori knowledge. the algorithm has been tested oil realistic Monte Carlo LHCb simulated events and it has been shown very powerful in detecting complex images full of rings. the tracking-independent algorithm Could be usefully employed after a track based approach to identify remaining trackless rings. (C) 2005 Elsevier Inc. All rights reserved.

关键词： RICH counters pattern recognition possibilistic clustering

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A subpath kernel for learning hierarchical image representations 10

A subpath kernel for learning hierarchical image representat...

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10th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2015

作者： Cui, Yanwei Chapel, Laetitia Lefèvre, Sébastien University Bretagne-Sud Vannes56000 France

ISBN: (纸本)9783319182230

Tree kernels have demonstrated their ability to deal with hierarchical data, as the intrinsic tree structure often plays a discriminative role. While such kernels have been successfully applied to various domains such as nature language processing and bioinformatics, they mostly concentrate on ordered trees and whose nodes are described by symbolic data. Meanwhile, hierarchical representations have gained increasing interest to describe image content. this is particularly true in remote sensing, where such representations allow for revealing different objects of interest at various scales through a tree structure. However, the induced trees are unordered and the nodes are equipped with numerical features. In this paper, we propose a new structured kernel for hierarchical image representations which is built on the concept of subpath kernel. Experimental results on both artificial and remote sensing datasets show that the proposed kernel manages to deal with the hierarchical nature of the data, leading to better classification rates. © Springer international Publishing Switzerland 2015.

关键词： Image classification

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Energy Minimization Methods in Computer Vision and pattern recognition - 5th international workshop, EMMCVPR 2005, Proceedings

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5th international workshop on Energy Minimization Methods in Computer Vision and pattern recognition, EMMCVPR 2005

ISBN: (纸本)3540302875

the proceedings contain 42 papers. the topics discussed include: adaptive simulated annealing for energy minimization problem in a marked point process application;a computational approach to Fisher information geometry with applications to image analysis;optimizing the Cauchy-Schwarz PDF distance for information theoretic, non-parametric clustering;color correction of underwater images for aquatic robot inspection;handling missing data in the computation of 3D affine transformations;geodesic image matching: a wavelet based energy minimization scheme;segmentation informed by manifold learning;and edge strength functions as shape priors in image segmentation.

关键词： Computer science

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Time Series pattern Discovery by Deep Learning and graph Mining 32nd

Time Series Pattern Discovery by Deep Learning and Graph Min...

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12th international workshop on Biological Knowledge Discovery from Data, BIOKDD 2021, 5th international workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2021, 3rd international workshop on Machine Learning and Knowledge graphs, MLKgraphs 2021, 1st international workshop on Artificial Intelligence for Clean, Affordable and Reliable Energy Supply, AI-CARES 2021, 1st international workshop on Time Ordered Data, ProTime2021 and 1st international workshop on AI System Engineering: Math, Modelling and Software, AISys2021 held at 32nd international Conference on Database and Expert Systems Applications, DEXA 2021

作者： Romanova, Alex Melenar LLC McLeanVA22101 United States

ISBN: (纸本)9783030871000

Outstanding success of CNN image classification affected using it as an instrument for time series classification. Powerful graph clustering methods have capabilities to come across entity relationships. In this study we propose time series pattern discovery approach as a hybrid of independent CNN image classification and graph mining. Our experiments are based on Electroencephalography (EEG) channel signals data from research of Alcoholic and Control person behaviors. For image classification we used techniques of transforming vectors to images on Gramian Angular Fields (GAF) and for graph mining we built time series graphs on pairs of vectors with high cosine similarities. We unlocked EEG time series patterns that not just validate differences in stimuli reactions of persons from Alcoholic or Control groups but also indicate similarities or dissimilarities between EEG channel signals located in different scalp landscape positions. © 2021, Springer Nature Switzerland AG.

关键词： Image classification

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Report on the first contest on graph matching algorithms for pattern search in biological databases 10

Report on the first contest on graph matching algorithms for...

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10th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2015

作者： Carletti, Vincenzo Foggia, Pasquale Vento, Mario Jiang, Xiaoyi Department of Information Engineering Electrical Engineering and Applied Mathematics University of Salerno Fisciano Italy Department of Computer Science University of Münster Münster Germany

ISBN: (纸本)9783319182230

graphs are a powerful data structure that can be applied to several problems in bioinformatics, and efficient graph matching is often a tool required for several applications that try to extract useful information from large databases of graphs. While graph matching is in general a NP-complete problem, several algorithms exist that can be fast enough on practical graphs. However, there is no single algorithm that is able to outperform the others on every kind of graphs, and so it is of paramount importance to assess the algorithms on graphs coming from the actual problem domain. To this aim, we have organized the first edition of the Contest on graph Matching Algorithms for pattern Search in Biological Databases, hosted by the ICPR2014 Conference, so as to provide an opportunity for comparing state-of-the-art matching algorithms on a new graph database built using several kinds of real-world graphs found in bioinformatics applications. the participating algorithms were evaluated with respect to both their computation time and their memory usage. this paper will describe the contest task and databases, will provide a brief outline of the participating algorithms, and will present the results of the contest. © Springer international Publishing Switzerland 2015.

关键词： Bioinformatics

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Face recognition System using SVM-based Classifier

Face Recognition System using SVM-Based Classifier

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5th IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems - Technology and Applications (IDAACS)

作者： Frolov, Igor Sadykhov, Rauf Belarusian State Univ Informat & Radioelect 6 P Brovka Str Minsk BELARUS United Inst Informat Problems Minsk BELARUS

ISBN: (纸本)9781424448814

the development of automatic visual control system is a very important research topic in computer vision. there is an complex task of development face identification system robust to the various quality of the images as light, face expression, glasses, beards, moustaches etc. We propose using the wavelet transformation algorithms for reduction the source data space. We have realized an expansion of pixels values to the whole intensity range and the equalization of histogram for the elimination of the intensity difference. the support vector machines technology has been used for the face recognition in our work.

关键词： Face identification pattern recognition support vector machines discrete wavelet transformation

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5th international Provenance and Annotation workshop, IPAW 2014

5th International Provenance and Annotation Workshop, IPAW 2...

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5th international Provenance and Annotation workshop, IPAW 2014

ISBN: (纸本)9783319164618

the proceedings contain 45 papers. the special focus in this conference is on Standardization of Provenance Models, Services, representations, Applications of Provenance, Provenance Management Architectures, Security and Privacy Implications of Provenance. the topics include: Generating synthetic PROV graphs with predictable structure;walking into the future with PROV pingback;regenerating and quantifying quality of benchmarking data using static and dynamic provenance;capturing and analyzing provenance of scripts;exploiting workflow provenance to surface scientific data provenance;auditing and maintaining provenance in software packages;a provenance-based policy control framework for cloud services;applying provenance to protect attribution in distributed computational scientific experiments;generating scientific documentation for computational experiments using provenance;computing location-based lineage from workflow specifications to optimize provenance queries;a lightweight provenance pingback and query service for web publications;provenance-based searching and ranking for scientific workflows;improving workflow design using abstract provenance graphs;early discovery of tomato foliage diseases based on data provenance and pattern recognition;enhancing provenance representation with knowledge based on NFR conceptual modeling;towards supporting provenance gathering and querying in different database approaches;challenges for provenance analytics over geospatial data;using well-founded provenance ontologies to query meteorological data and provenance support for medical research.

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Fifth international workshop on pattern recognition

Fifth International Workshop on Pattern Recognition

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5th international workshop on pattern recognition, IWPR 2020

ISBN: (纸本)9781510638631

the proceedings contain 18 papers. the topics discussed include: improved hierarchical models for non-native Chinese handwriting recognition using hidden conditional random fields;a framework for multimodal sign language recognition under small sample based on key-frame sampling;a classification method for rotor imbalance fault with ISFLA-SVM;facial expression recognition based on feature fusion;improving visual question answering with pre-trained language modeling;feature detection based on linear prediction residual for spoofing countermeasures of speaker verification system;classification of defaced occlusion plates based on convolutional neural network;research of road scene object detection algorithm based on mobile platform;and improved YOLO model with multi-feature fully convolutional network for object detection.

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