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检索条件"任意字段=7th International Workshop on Graph-Based Representations in Pattern Recognition"

共 197 条记录，以下是81-90 订阅

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An algorithm for maximum common subgraph of planar triangulation graphs

An algorithm for maximum common subgraph of planar triangula...

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9th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2013

作者： Lu, Yao Bunke, Horst Liu, Cheng-Lin National Lab. of Pattern Recognition Institute of Automation Chinese Academy of Sciences China University of Bern Switzerland

ISBN: (纸本)9783642382208

We propose a new fast algorithm for solving the Maximum Common Subgraph (MCS) problem. MCS is an NP-complete problem. In this paper, we focus on a special class of graphs, i.e. Planar Triangulation graphs, which are commonly used in computer vision, pattern recognition and graphics. By exploiting the properties of Planar Triangulation graphs and restricting the problem to connected MCS, for two such graphs of size n and m and their maximum common subgraph of size k, our algorithm solves the MCS problem approximately with time complexity O(nmk). © 2013 Springer-Verlag.

关键词： pattern recognition

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On-line signature verification: An approach based on cluster representations of global features

On-line signature verification: An approach based on cluster...

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7th international Conference on Advances in pattern recognition, ICAPR 2009

作者： Guru, D.S. Prakash, H.N. Manjunath, S. Department of Studies in Computer Science University of Mysore Mysore 570 006 India

ISBN: (纸本)9780769535203

In this paper, we propose a new method of representation of on-line signatures by clustering of signatures. Our idea is to provide better representation by clustering of signatures based on global features. Global features of signatures of each cluster are used to form an interval valued feature vector which is a symbolic representation for a cluster. based on cluster representation, we propose methods of signature verification. We compare the feasibility of the proposed representation scheme for signature verification on a large MCYT-signature database [1] of 16500 signatures. Unlike other signature verification methods, the proposed method is simple and efficient and in addition, shows a remarkable reduction in EER. © 2009 IEEE.

关键词： Fuzzy C-means (FCM) clustering Global features On-line signature verification Symbolic feature vector

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Towards unitary representations for graph matching

Towards unitary representations for graph matching

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5th IAPR international workshop on graph-based representations in pattern recognition, GbRPR 2005

作者： Emms, David Severini, Simone Wilson, Richard C. Hancock, Edwin R. Departments of Computer Science and Mathematics United Kingdom Department of Computer Science University of York York Y010 5DD United Kingdom

In this paper we explore how a spectral technique suggested by quantum walks can be used to distinguish non-isomorphic cospectral graphs. Reviewing ideas from the field of quantum computing we recall the definition of the unitary matrices inducing quantum walks. We show how the spectra of these matrices are related to the spectra of the transition matrices of classical walks. Despite this relationship the behaviour of quantum walks is vastly different from classical walks. We show how this leads us to define a new matrix whose spectrum can be used to distinguish between graphs that are otherwise indistinguishable by standard spectral methods. © Springer-Verlag Berlin Heidelberg 2005.

关键词： graph theory

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A fast matching algorithm for graph-based handwriting recognition

A fast matching algorithm for graph-based handwriting recogn...

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9th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2013

作者： Fischer, Andreas Suen, Ching Y. Frinken, Volkmar Riesen, Kaspar Bunke, Horst Centre for Pattern Recognition and Machine Intelligence Concordia University 1455 de Maisonneuve Blvd West Montreal QC H3G 1M8 Canada Computer Vision Center Dept. of Computer Science Universitat Autònoma de Barcelona 08193 Bellaterra Spain Institute for Informations Systems University of Applied Sciences and Arts Northwestern Switzerland Riggenbachstrasse 16 4600 Olten Switzerland Institute of Computer Science and Applied Mathematics University of Bern Neubrückstrasse 10 3012 Bern Switzerland

ISBN: (纸本)9783642382208

the recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between structural representation and statistical classification by means of vector space embedding. this approach has shown a high performance in terms of accuracy but had shortcomings in terms of computational speed. the time complexity of the Hungarian algorithm that is used to approximate the edit distance between two handwriting graphs is demanding for a real-world scenario. In this paper, we propose a faster graph matching algorithm which is derived from the Hausdorff distance. On the historical Parzival database it is demonstrated that the proposed method achieves a speedup factor of 12.9 without significant loss in recognition accuracy. © 2013 Springer-Verlag.

关键词： Vector spaces

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On Lipschitz embeddings of graphs

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12th international Conference on Knowledge-based Intelligent Information and Engineering Systems

作者： Riesen, Kaspar Bunke, Horst Univ Bern Inst Comp Sci & Appl Math CH-3012 Bern Switzerland

ISBN: (纸本)9783540855620

In pattern recognition and related fields, graph based representations offer a versatile alternative to the widely used feature vectors. therefore, an emerging trend of representing objects by graphs can be observed. this trend is intensified by the development of novel approaches in graph based machine learning, such as graph kernels or graph embedding techniques. these procedures overcome a major drawback of graphs, which consists in a serious lack of algorithms for classification and clustering. the present;paper is inspired by the idea of representing graphs by means of dissimilarities and extends previous work to the more general setting of Lipschitz embeddings. In all experimental evaluation we empirically confirm that classifiers relying oil the original graph distances call be outperformed by a classification system using the Lipschitz embedded graphs.

关键词： pattern recognition

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Generalised syntactic pattern recognition as a unifying approach in image analysis 7th

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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

作者： Venguerov, Mark Cunningham, Pádraig POINT Information Systems Ltd. Ireland AIG Department of Computer Science Trinity College University of Dublin Ireland

ISBN: (纸本)3540648585

In this paper we analyse theoretical foundations of syntactic pattern recognition and its relationships with mathematical linguistics, structural pattern recognition, and statistical pattern recognition. We point out that all the above mentioned methods are based on two fundamental operations: the combination of parts into wholes and abstraction. We provide examples of those operations in different contexts. Finally, we note that at this level of generalisation, all three main approaches to pattern recognition (structural, statistical and syntactic) can be merged into one powerful method. We outline a system based on these principles and intended to be used for the recognition of unconstrained handwriting. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Syntactics

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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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6th international workshop on Structural and Syntactical pattern recognition, SSPR 1996

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6th international workshop on Structural and Syntactical pattern recognition, SSPR 1996

ISBN: (纸本)3540615776

the proceedings contain 39 papers. the special focus in this conference is on Grammars, Languages, Morphology and Semantic Nets. the topics include: Efficient recognition of a class of context-sensitive languages described by augmented regular expressions;optimal and information theoretic syntactic pattern recognition for traditional errors;the morphic generator grammatical inference methodology and multilayer perceptrons;a hybrid approach to acoustic modeling;two different approaches for cost-efficient viterbi parsing with error correction;bounded parallelism in array grammars used for character recognition;comparison between the inside-outside algorithm and the viterbi algorithm for stochastic context-free grammars;generalized morphological operators applied to map-analysis;extended cascade-correlation for syntactic and structural pattern recognition;including geometry in graph representations;a quadratic-time graph isomorphism algorithm and its applications;an evidential merit function to guide search in a semantic network based image analysis system;inexact graph matching with genetic search;automatic recognition of bidimensional models learned by grammatical inference in outdoors scenes;signal decomposition by multiscale learning algorithms;structural learning of character patterns for on-line recognition of hand-written Japanese characters;recognition of hand-printed characters using induct machine learning;opponent color processing based on neural models;invariants and fixed structures lead the way to change;representing shape by line patterns;surface skeletonization of volume objects;peculiarities of structural analysis of image contours under various orders of scanning and a structural analysis of curve deformation by discontinuous transformations.

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Proceedings of the 8th SIGHAN workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th international Joint Conference on Natural Language Processing, ACL IJCNLP 2015

Proceedings of the 8th SIGHAN Workshop on Chinese Language P...

引用

8th SIGHAN workshop on Chinese Language Processing, SIGHAN 2015

ISBN: (纸本)9781941643570

the proceedings contain 28 papers. the topics discussed include: sequential annotation and chunking of Chinese discourse structure;create a manual Chinese word segmentation dataset using crowdsourcing method;Chinese named entity recognition with graph-based semi-supervised learning model;sentence selection for automatic scoring of mandarin proficiency;ACBiMA: advanced Chinese bi-character word morphological analyzer;introduction to SIGHAN 2015 bake-off for Chinese spelling check;word vector/conditional random field-based Chinese spelling error detection for SIGHAN-2015 evaluation;introduction to a proofreading tool for Chinese spelling check task of SIGHAN-8;overview of topic-based Chinese message polarity classification in SIGHAN 2015;a joint model for Chinese microblog sentiment analysis;learning salient samples and distributed representations for topic-based Chinese message polarity classification;and an combined sentiment classification system for SIGHAN-8.

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IWCLUL 2021 - 7th international workshop on Computational Linguistics of Uralic Languages, Proceedings

IWCLUL 2021 - 7th International Workshop on Computational Li...

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7th international workshop on Computational Linguistics of Uralic Languages, IWCLUL 2021

ISBN: (纸本)9781954085824

the proceedings contain 8 papers. the topics discussed include: the current state of Finnish NLP;integrating pattern- and fact-based fake news detection via model preference learning;a second pandemic? analysis of fake news about COVID-19 vaccines in Qatar;WRENCH: a comprehensive benchmark for weak supervision;cluster-based mention typing for named entity disambiguation;named entity recognition and classification on historical documents: a survey;an algorithm for generating gap-fill multiple choice questions of an expert system;and automated fact-checking: a survey.

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