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7th international workshop on graph-based representations in pattern recognition

作者： Gonzalez-Diaz, Rocio Ion, Adrian Iglesias-Ham, Mabel Kropatsch, Walter G. Univ Seville Dept Appl Math Seville Spain CENATAV Pattern Recognit Dept Havana Cuba Vienna Univ Technol Pattern Recognit & Image Proc Grp A-1040 Vienna Austria

ISBN: (纸本)9783642021237

Structural pattern recognition describes and classifies data based on the relationships of features and parts. Topological invariants, like the Euler number, characterize the structure of objects of any dimension. Cohomology can provide more refined algebraic invariants to a topological space that does homology. It assigns 'quantities' to the chains used in homology to characterize holes of any dimension. graph pyramids can be used to describe subdivisions of the same object at multiple levels of detail. this paper presents cohomology in the context of structural pattern recognition and introduces an algorithm to efficiency compute representative cocycles (the basic elements of cohomology) in 2D using a graph pyramid. Extension to nD and application in the context of pattern recognition are discussed.

关键词： graph pyramids representative cocycles of cohomology generators

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Approximating TSP solution by MST based graph pyramid

Approximating TSP solution by MST based graph pyramid

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6th international workshop on graph-based representations in pattern recognition

作者： Haxhimusa, Yll Kropatsch, Walter G. Pizlo, Zygmunt Ion, Adrian Lehrbaum, Andreas Vienna Univ Technol Fac Informat Inst Comp Aided Automat Pattern Recognit & Image Proc Grp A-1040 Vienna Austria Purdue Univ Dept Physiol Sci W Lafayette IN 47907 USA

ISBN: (纸本)9783540729020

the traveling salesperson problem (TSP) is difficult to solve for input instances with large number of cities. Instead of finding the solution of an input with a large number of cities, the problem is approximated into a simpler form containing smaller number of cities, which is then solved optimally. graph pyramid solution strategies, in a bottom-up manner using Boruvka's minimum spanning tree, convert a 2D Euclidean TSP problem with a large number of cities into successively smaller problems (graphs) with similar layout and solution, until the number of cities is small enough to seek the optimal solution. Expanding this tour solution in a top-down manner to the lower levels of the pyramid approximates the solution. the new model has an adaptive spatial structure and it simulates visual acuity and visual attention. the model solves the TSP problem sequentially, by moving attention from city to city with the same quality as humans. graph pyramid data structures and processing strategies are a plausible model for finding near-optimal solutions for computationally hard pattern recognition problems.

关键词： graph theory

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Data-driven Latent graph Structure Learning for Diagnosis of Alzheimer's Syndrome 26

Data-driven Latent Graph Structure Learning for Diagnosis of...

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

作者： Wang, Jianjia Wu, Chong Shanghai Univ Shanghai Inst Adv Commun & Data Sci Sch Comp Engn & Sci Shanghai Peoples R China Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Complex systems often have a latent graph structure. Studying the underlying graph structure will help us to analyze the mechanisms of complex phenomena. However, it is a challenging problem to learn effective graph structures from the data and apply them to downstream tasks. In this paper, we propose an end-to-end graph learning approach for Alzheimer's syndrome diagnosis based on functional magnetic resonance imaging (fMRI) data of brain regions, which is completely data-driven. the interactions between time-series of each brain region are represented as graph structures, and a multi-head attention mechanism is used to update the representations of the nodes. then, the graph structures are obtained from the feature sampling of the edges. Finally, the learned graph structure is combined with the left-out time-series data features and the node prior to completing the classification task of the brain network. In comparison with the latest research methods, our approach achieves higher classification accuracy.

关键词： Image edge detection Functional magnetic resonance imaging pattern recognition Task analysis Alzheimer's disease Complex systems

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Including geometry in graph representations: A quadratic-time graph isomorphism algorithm and its applications 6th

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

作者： Jiang, X.Y. Bunke, H. Dept. of Computer Science University of Bern Neubrückstrasse 10 BernCH-3012 Switzerland

ISBN: (纸本)3540615776

In graph representations of objects, geometric information is typically lost. this has forced researchers to use graph matching techniques that are intended to handle general graphs. By encoding the lost geometric information into graph representations, however, we can apply more efficient algorithms for constrained graphs. In this paper we introduce an edge ordering property that is satisfied in many applications. Given this property, the graph isomorphism problem is solvable in quadratic time. We discuss three concrete applications that can be reduced to the graph isomorphism problem and can thus profit from the quadratic-time graph isomorphism algorithm. the improved performance is demonstrated by simulation experiments. © Springer-Verlag Berlin Heidelberg 1996.

关键词： Geometry

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On Computing Canonical Subsets of graph-based Behavioral representations

On Computing Canonical Subsets of Graph-Based Behavioral Rep...

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7th international workshop on graph-based representations in pattern recognition

作者： Mankowski, Walter C. Bogunovich, Peter Shokoufandeh, Ali Salvucci, Dario D. Drexel Univ Dept Comp Sci Philadelphia PA 19104 USA

ISBN: (纸本)9783642021237

the collection of behavior protocols is a common practice in human factors research, but the analysis of these large data sets has always been a tedious and time-consuming process. We are interested in automatically finding canonical behaviors: a small subset of behavioral protocols that is most representative of the full data set, providing a view of the data with as few protocols as possible. Behavior protocols often have a natural graph-based representation, yet there has been little work applying graph theory to their study. In this paper we extend our recent algorithm by taking into account the graph topology induced by the paths taken through the space of possible behaviors. We applied this technique to find canonical web-browsing behaviors for computer users. By comparing identified canonical sets to a ground truth determined by expert human coders. we found that this graph-based metric outperforms our previous metric based on edit distance.

关键词： graph theory

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Optimum-Path Forest based on k-connectivity: theory and applications

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pattern recognition LETTERS 2017年第Feb.1期87卷 117-126页

作者： Papa, Joao Paulo Nachif Fernandes, Silas Evandro Falcao, Alexandre Xavier Sao Paulo State Univ Dept Comp Av Eng Luiz Edmundo Carrijo Coube BR-17033360 Bauru SP Brazil Univ Fed Sao Carlos Dept Comp Rod Washington LuisKm 235 BR-13565905 Sao Carlos SP Brazil Univ Estadual Campinas Inst Comp Av Albert Einstein 1251 BR-13083852 Campinas SP Brazil

graph-based pattern recognition techniques have been in the spotlight for many years, since there is a constant need for faster and more effective approaches. Among them, the Optimum-Path Forest (OPF) framework has gained considerable attention in the last years, mainly due to the promising results obtained by OPF-based classifiers, which range from unsupervised, semi-supervised and supervised learning. In this paper, we consider a deeper theoretical explanation concerning the supervised OPF classifier with k-neighborhood (OPFk), as well as we proposed two different training and classification algorithms that allow OPFk to work faster. the experimental validation against standard OPF and Support Vector Machines also validates the robustness of OPFk in real and synthetic datasets. (C) 2016 Elsevier B.V. All rights reserved.

关键词： pattern classification Optimum-Path Forest Supervised learning

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Fast test pattern generation for sequential circuits using decision diagram representations

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JOURNAL OF ELECTRONIC TESTING-thEORY AND APPLICATIONS 2000年第3期16卷 213-226页

作者： Raik, J Ubar, R Tallinn Univ Technol Dept Comp Engn EE-12618 Tallinn Estonia

the paper presents a novel hierarchical approach to test pattern generation for sequential circuits based on an input model of mixed-level decision diagrams. A method that handles, both, data and control parts of the design in a uniform manner is proposed. the method combines deterministic and simulation-based techniques. On the register-transfer level, deterministic path activation is combined with simulation based-techniques used for constraints solving. the gate-level local test patterns for components are randomly generated driven by high-level constraints and partial path activation solutions. Experiments show that high fault coverages for circuits with complex sequential structures can be achieved in a very short time by using this approach.

关键词： hierarchical test pattern generation sequential circuits register-transfer level decision diagrams

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A Survey on Applications of Bipartite graph Edit Distance 11th

A Survey on Applications of Bipartite Graph Edit Distance

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11th IAPR-TC15 international workshop on graph-based representations in pattern recognition (GbRPR)

作者： Stauffer, Michael Tschachtli, thomas Fischer, Andreas Riesen, Kaspar Univ Appl Sci & Arts Northwestern Switzerland Inst Informat Syst Riggenbachstr 16 CH-4600 Olten Switzerland Univ Fribourg Dept Informat CH-1700 Fribourg Switzerland Univ Appl Sci & Arts Western Switzerland Inst Complex Syst CH-1705 Fribourg Switzerland Univ Pretoria Dept Informat Pretoria South Africa

ISBN: (纸本)9783319589619;9783319589602

About ten years ago, a novel graph edit distance framework based on bipartite graph matching has been introduced. this particular framework allows the approximation of graph edit distance in cubic time. this, in turn, makes the concept of graph edit distance also applicable to larger graphs. In the last decade the corresponding paper has been cited more than 360 times. Besides various extensions from the methodological point of view, we also observe a great variety of applications that make use of the bipartite graph matching framework. the present paper aims at giving a first survey on these applications stemming from six different categories (which range from document analysis, over biometrics to malware detection).

关键词： Applications of bipartite graph matching graph-based pattern representations

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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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A Recursive Embedding Approach to Median graph Computation

A Recursive Embedding Approach to Median Graph Computation

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7th international workshop on graph-based representations in pattern recognition

作者： Ferrer, M. Karatzas, D. Valveny, E. Bunke, H. CSIC UPC Inst Robot & Informat Ind C Llorens Artigas 4-6 E-08028 Barcelona Spain Univ Autonoma Barcelona Ctr Vis Comp E-08193 Bellaterra Spain Univ Bern Inst Comp Sci & Appl Math CH-3012 Bern Switzerland

ISBN: (纸本)9783642021237

the median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper We present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments oil three databases show that this new approach is able to obtain better medians than the previous existing approaches.

关键词： graphic methods

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