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检索条件"任意字段=6th International Workshop on Graph-Based Representations in Pattern Recognition"

共 215 条记录，以下是111-120 订阅

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Optimal line and Arc detection on run-length representations

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6th international workshop on graphic recognition

作者： Keysers, Daniel Breuel, thomas M. DFKI GmbH German Res Ctr Artificial Intelligence Image Understanding & Pattern Recognit Res Grp D-67663 Kaiserslautern Germany Univ Kaiserslautern D-67663 Kaiserslautern Germany

ISBN: (纸本)3540347119

the robust detection of lines and arcs in scanned documents or technical drawings is an important problem in document image understanding. We present a new solution to this problem that works directly on run-length encoded data. the method finds globally optimal solutions to parameterized thick line and are models. Line thickness is part of the model and directly used during the matching process. Unlike previous approaches, it does not require any thinning or other preprocessing steps, no computation of the line adjacency graphs, and no heuristics. Furthermore, the only search-related parameter that needs to be specified is the desired numerical accuracy of the solution. the method is based on a branch-and-bound approach for the globally optimal detection of these geometric primitives using runs of black pixels in a bi-level image. We present qualitative and quantitative results of the algorithm on images used in the 2003 and 2005 GREC arc segmentation contests.

关键词： graphics recognition line drawings technical drawings branch-and-bound algorithms

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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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Simulation data mining for functional test pattern justification

Simulation data mining for functional test pattern justifica...

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6th international workshop on Microprocessor Test and Verification

作者： Wen, Charles H. -P. Wang, Li-C. Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)9780769526270

In simulation-based functional verification, composing and debugging testbenches can be tedious and time-consuming. A simulation-based data-mining approach [3] was proposed as an alternative for functional test pattern generation. However, the core of the approach is in solving Boolean learning, which is the problem of learning Boolean functions from bit-level simulation data. In this paper an efficient data mining engine based on novel decision-diagram(DD) based learning approaches is presented. We compare the DD-based learning approaches to other known methods such as Nearest Neighbor and Support Vector Machine. We show that the new Boolean data miner is efficient for practical use and the learned results can provide compact and accurately approximate representations of Boolean functions. Finally, we show that the proposed methodology incorporated with the current Boolean data miner can achieve a high fault coverage (95.36%) on the OpenRISC 1200 microprocessor demonstrating the effectiveness of our approach.

关键词： Data mining

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the Effect of Moving Windows on Software Effort Estimation: Comparative Study with CART 6

The Effect of Moving Windows on Software Effort Estimation: ...

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6th international workshop on Empirical Software Engineering in Practice (IWESEP)

作者： Amasaki, Sousuke Lokan, Chris Okayama Prefectural Univ Dept Syst Engn Okayama 7191197 Japan UNSW Canberra Sch Engn & Informat Technol Canberra ACT 2600 Australia

ISBN: (纸本)9781479966660

BACKGROUND: Several studies in software effort estimation have found that it can be effective to use a window of recent projects as training data for building an effort estimation model. the previous studies evaluated the use of a window with popular estimation models: linear regression (LR) and estimation by analogy (EbA). Many effort estimation models have been proposed, and the generality of windowing approach still remains uncertain for other effort estimation models, especially for those based on different theory. OBJECTIVE: this study investigates the effect of using a window on estimation accuracy with Classification and regression trees (CART). CART was recently found as a good performance method, and is based on a different theory from LR and EbA. MEthOD: We compared the estimation accuracy of a windowing approach and growing approach with the same data set and procedure as the past studies. RESULTS: there is a difference in the estimation accuracy between using a window and not using a window. However, the effctive range of using windows on CART is narrower than that on LR. CONCLUSIONS: Windowing is also effective with CART. However, the range of effectiveness is narrower. the results contribute to the generality of the effectiveness of windowing approach.

关键词： pattern classification regression analysis software development management CART EbA LR classification and regression trees effort estimation models estimation by analogy linear regression moving windows software effort estimation windowing approach Accuracy Estimation Linear regression Market research Size measurement Software Testing effort estimation classification and regression trees Linear Regression windows dimensional measurement Software development management market research cart window windows multiprogramming computer software pattern recognition regression analysis computer programs

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Inexact multisubgraph matching using graph eigenspace and clustering models 9th

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Joint IAPR 9th international workshop on Structural and Syntactic pattern recognition, SSPR 2002 and 4th international workshop on Statistical Techniques in pattern recognition, SPR 2002

作者： Kosinov, Serhiy Caelli, Terry The University of Alberta EdmontonABT6G 2H1 Canada

ISBN: (纸本)3540440119

In this paper we show how inexact multisubgraph matching can be solved using methods based on the projections of vertices (and their connections) into the eigenspaces of graphs - and associated clustering methods. Our analysis points to deficiencies of recent eigenspectra methods though demonstrates just how powerful full eigenspace methods can be for providing filters for such computationally intense problems. Also presented are some applications of the proposed method to shape matching, information retrieval and natural language processing. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Cluster analysis

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36th international Conference on Conceptual Modeling, ER 2017 held in Conjuction with the 3rd international workshop on Modeling for Ambient Assistance and Healthy Ageing, AHA 2017, 6th international workshop on Modeling and Management of Big Data, MoBiD 2017, 4th international workshop on Conceptual Modeling in Requirements and Business Analysis, MREBA 2017, 5th international workshop on Ontologies and Conceptual Modeling, OntoCom 2017 and 4th workshop on Quality of Models and Models of Quality, QMMQ 2017

36th International Conference on Conceptual Modeling, ER 201...

引用

36th international Conference on Conceptual Modeling, ER 2017 held in Conjuction with the 3rd international workshop on Modeling for Ambient Assistance and Healthy Ageing, AHA 2017, 6th international workshop on Modeling and Management of Big Data, MoBiD 2017, 4th international workshop on Conceptual Modeling in Requirements and Business Analysis, MREBA 2017, 5th international workshop on Ontologies and Conceptual Modeling, OntoCom 2017 and 4th workshop on Quality of Models and Models of Quality, QMMQ 2017

ISBN: (纸本)9783319706245

the proceedings contain 22 papers. the special focus in this conference is on Conceptual Modeling. the topics include: Towards an ontology for strategic decision making: the Case of quality in rapid software development projects;detecting bad smells of refinement in goal-oriented requirements analysis;Requirements engineering for data warehouses (RE4DW): From strategic goals to multidimensional model;towards formal strategy analysis with goal models and semantic web technologies;assisting process modeling by identifying business process elements in natural language texts;Using multidimensional concepts for detecting problematic Sub-KPIs in analysis systems;automatically annotating business process models with ontology concepts at design-time;OPL-ML: A modeling language for representing ontology pattern languages;Evaluating quality issues in BPMN models by extending a technical debt software platform;data modelling for dynamic monitoring of vital signs: Challenges and perspectives;utility-driven data management for data-intensive applications in fog environments;Assessing the positional planimetric accuracy of DBpedia georeferenced resources;Assessing the completeness evolution of DBpedia: A case study;towards care systems using model-driven adaptation and monitoring of autonomous multi-clouds;clustering event traces by behavioral similarity;goal-based selection of visual representations for big data analytics;A four V’s design approach of NoSQL graph databases;towards efficient and informative omni-channel customer relationship management;stream clustering of chat messages with applications to twitch streams;towards consistent demarcation of enterprise design domains.

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Database Systems for Advanced Applications. DASFAA 2021 international workshops 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Christian S. Jensen Ee-Peng Lim De-Nian Yang Chia-Hui Chang Jianliang Xu Wen-Chih Peng Jen-Wei Huang Chih-Ya Shen

ISBN: (数字)9783030732165

ISBN: (纸本)9783030732158

the 29 revised full papers presented in this book were carefully reviewed and selected from 84 submissions.;6th international workshop on Big Data Quality Management (BDQM 2021);5th international workshop on graph Data Management and Analysis (GDMA 2021);First international workshop on Machine Learning and Deep Learning for Data Security Applications (MLDLDSA 2021);6th international workshop on Mobile Data Management, Mining, and Computing on Social Network (MobiSocial 2021);2021 international workshop on Mobile Ubiquitous Systems and Technologies (MUST 2021)

关键词： Data Mining and Knowledge Discovery Computer Communication Networks Data Structures and Information theory Artificial Intelligence Computer Imaging, Vision, pattern recognition and graphics Computer Systems Organization and Communication Networks

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Matching Functional Connectivity patterns for Spatial Correspondence Detection in fMRI Registration

Matching Functional Connectivity Patterns for Spatial Corres...

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6th international workshop on Medical Imaging and Augmented Reality (MIAR) / 8th international workshop on Augmented Reality for Computer- Assisted Interventions (AE-CAI)

作者： Tang, Zhenyu Jiang, Di Li, Hongming Fan, Yong Chinese Acad Sci Inst Automat Brainnetome Ctr Beijing 100190 Peoples R China

ISBN: (纸本)9783642408427;9783642408434

A novel method is proposed to match functional connectivity patterns represented by graphs for spatial registration of fMRI data. Different from existing functional connectivity pattern based registration methods that detect corresponding functional units across different subjects by minimizing their difference in functional connectivity strength, our method adopts a graph representation to characterize functional connectivity information among all voxels in fMRI data of each subject, then detects spatial correspondence between subjects using graph matching. To integrate information of both functional connectivity strength and spatial relations, the graph representation of functional connectivity information of fMRI data models each voxel as one graph node and connects each pair of graph nodes with an edge weighted by their functional connectivity strength measure, estimated as correlation coefficient between their functional signals. To make the graph matching computationally feasible, an iterative matching strategy with stochastic resampling is proposed to match graphs of spatially distributed local functional connectivity patterns and subsequently to drive the image registration iteratively. the proposed method has been validated by registering resting state fMRI data of 20 healthy subjects. the validation experiment results have demonstrated that our method can achieve improved inter-subject functional consistency. A comparison experiment result has further indicated that the proposed method can achieve better performance than existing methods.

关键词： fMRI registration graph matching functional connectivity pattern

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CEUR workshop Proceedings

CEUR Workshop Proceedings

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6th international workshop "What can FCA do for Artificial Intelligence"?, FCA4AI 2018

the proceedings contain 11 papers. the topics discussed include: inductive reasoning with conceptual space representations;an answer set programming environment for high-level specification and visualization of FCA;three approaches for mining definitions from relational data in the web of data;relational proportions between objects and attributes;the theory and practice of coupling formal concept analysis to relational databases;generalized metrics with applications to ratings and formal concept analysis;binary lattices;biclustering based on FCA and partition pattern structures for recommendation systems;and combining concept annotation and pattern structures for guiding ontology mapping.

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4th international workshop on Energy Minimization Methods in Computer Vision and pattern recognition, EMMCVPR 2003

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4th international workshop on Energy Minimization Methods in Computer Vision and pattern recognition, EMMCVPR 2003

ISBN: (纸本)3540404988

the proceedings contain 39 papers. the special focus in this conference is on Unsupervised Learning, Matching, Probabilistic Modelling, Segmentation, Grouping, Shape Modelling and Reconstruction. the topics include: Stochastic search for optimal linear representations of images on spaces with orthogonality constraints;curve matching using the fast marching method;EM algorithm for clustering an ensemble of graphs with comb matching;information force clustering using directed trees;active sampling strategies for multihypothesis testing;likelihood based hierarchical clustering and network topology identification;learning mixtures of tree-unions by minimizing description length;hierarchical annealing for random image synthesis;semi-supervised image segmentation by parametric distributional clustering;path variation and image segmentation;a fast snake segmentation method applied to histopathological sections;a compositionality architecture for perceptual feature grouping;using prior shape and points in medical image segmentation;separating a texture from an arbitrary background using pair wise grey level cooccurrences;surface recovery from 3D point data using a combined parametric and geometric flow approach;curvature vector flow to assure convergent deformable models for shape modelling;a MAP estimation algorithm using IIR recursive filters;estimation of rank deficient matrices from partial observations;contextual and non-combinatorial approach to feature extraction;generalized multi-camera scene reconstruction using graph cuts and graph matching using spectral seriation.

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