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4th IAPR international workshop on graph based representations in pattern recognition, GbRPR 2003

作者： Qiu, Huaijun Hancock, Edwin R. Department of Computer Science University of York Heslington YorkYO10 5DD United Kingdom

ISBN: (纸本)354040452X

Although inexact graph-matching is a problem of potentially exponential complexity, the problem may be simplified by decomposing the graphs to be matched into smaller subgraphs. If this is done, then the process may cast into a hierarchical framework or cast in a way which is amenable to parallel computation. In this paper we demonstrate how the Fiedler-vector can be used to partition graphs for the purposes of decomposition. We show how the resulting subgraphs can be matched using a variety of algorithms. We demonstrate the utility of the resulting graph-matching method on both real work and synthetic data. Here it proves to provide results which are comparable with a number of stateof- the-art graph matching algorithms. © Springer-Verlag Berlin Heidelberg 2003.

关键词： pattern matching

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An sEMG-based Human-Robot Interface for Robotic Hands Using Machine Learning and Synergies

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IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY 2018年第7期8卷 1149-1158页

作者： Meattini, R. Benatti, S. Scarcia, U. De Gregorio, D. Benini, L. Melchiorri, C. Univ Bologna Dept Elect Elect & Informat Engn I-40126 Bologna Italy Swiss Fed Inst Technol Dept Informat Technol & Elect Engn CH-8092 Zurich Switzerland

Developing natural control strategies represents an intriguing challenge in the design of human-robot interface (HRI) systems. the teleoperation of robotic grasping devices, especially in industrial, rescue, and aerospace applications, is mostly based on nonintuitive approaches, such as remote controllers. On the other hand, recent research efforts target solutions that mimic the human ability to manage multifinger grasps and finely modulate grasp impedance. Since electromyography (EMG) contains information about human motion control, it is possible to leverage such neuromuscular knowledge to teleoperate robotic hands for grasping tasks. In this paper, we present an HRI system based on eight fully differential EMG sensors connected to a wearable sensor node for acquisition and processing. By virtue of a novel bio-inspired approach, the embedded myocontroller merges pattern recognition and factorization techniques to combine a natural selection of the robotic hand configuration with the proportional control of the related grasps. the HRI system has been fully designed, implemented, and tested on two robotic hands: a dexterous anthropomorphic hand and a three-fingered industrial gripper mounted on a robotic manipulator. the results of the test performed on four able-bodied subjects show success rates greater than 90% reached in grasping objects that require different hand shapes and impedance regulations for the task completion. the outcomes also show that the users modulate the bio-inspired degrees of control in a natural manner, proving the pertinence of the proposed system for an effective human-like control of robotic grasping devices in a wearable form factor.

关键词： Electromyography (EMG) sensors embedded systems human-robot interface (HRI) industrial gripper grasping non-negative matrix factorization (NMF) pattern recognition robotic hands

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A pretopological approach for pattern classification with reject options 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： Frélicot, Carl Emptoz, Hubert Université de La Rochelle Laboratoire d’Informatique et d’Imagerie Industrielle La Rochelle Cedex 117042 France I.N.S.A. de Lyon Laboratoire de Reconnaissance des Formes et Vision Villeurbanne Cedex69621 France

ISBN: (纸本)3540648585

In this paper, we present a pretopological approach for pattern classification with reject options. the pretopological approach, based on growing c-neighborhoods, already has proved its efficiency in reducing computation time and storage requirements compared to a k-Nearest Neighbors approach. By including ambiguity and distance reject options, we give to such an approach more adaptability to real classification problems for which classes generally are not clearly separable and/or not completely known. In order to control both types of rejection, the proposed classifier needs a unique parameter to be fixed whereas two parameters generally are necessary (one for each reject type). We also have observed that the behavior of the classifier (depending of the parameter value) with respect to both kinds of rejection is similar to the behavior of well-known rejection-based classifiers proposed so far in the literature. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Nearest neighbor search

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graph clustering using the weighted minimum common supergraph

Graph clustering using the weighted minimum common supergrap...

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4th IAPR international workshop on graph based representations in pattern recognition, GbRPR 2003

作者： Bunke, Horst Foggia, P. Guidobaldi, C. Vento, M. Institut für Informatik und angwandte Mathematik Universität Bern Neubrückstrasse 10 BernCH-3012 Switzerland Dipartimento di Informatica e Sistemistica Università di Napoli "Federico II" Via Claudio 21 NapoliI-80125 Italy Dipartimento di Ingegneria dell’Informazione ed Ingegneria Elettrica Università di Salerno via P.te Don Melillo FiscianoSAI-84084 Italy

ISBN: (纸本)354040452X

graphs are a powerful and versatile tool useful for representing patterns in various subfields of science and engineering. In many applications, for example, in pattern recognition and computer vision, it is required to measure the similarity of objects for clustering similar patterns. In this paper a new structural method, the Weighted Minimum Common Supergraph (WMCS), for representing a cluster of patterns is proposed. Using this method it becomes easy to extract the common information shared in the patterns of a cluster and separate this information from noise and distortions that usually affect graphs representing real objects. Moreover, experimental results show that WMCS is suitable for performing graph clustering. © Springer-Verlag Berlin Heidelberg 2003.

关键词： pattern recognition

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Multiple Classifier Systems - 7th international workshop, MCS 2007, Proceedings

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7th international workshop on Multiple Classifier Systems, MCS 2007

ISBN: (纸本)9783540724810

the proceedings contain 51 papers. the topics discussed include: combining pattern recognition modalities at the sensor level via kernel fusion;deriving the kernel from training data;classifiers fusion in recognition of wheat varieties;an improved random subspace method and its application to EEG signal classification;confidence based gating of colour features for face authentication;serial fusion of fingerprint and face matchers;information theoretic combination of classifiers with application to AdaBoost;interactive boosting for image classification;selecting diversifying heuristics for cluster ensembles;classifier ensembles for vector space embedding of graphs;cascading for nominal data;feature subspace ensembles: a parallel classifier combination scheme using feature selection;optimal classifier combination rules for verification and identification systems;an experimental study on rotation forest ensembles;and biometric person authentication is a multiple classifier problem.

关键词： Multi agent systems

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A multimodal Windows malware detection method based on hybrid analysis and graph representations 7

A multimodal Windows malware detection method based on hybri...

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7th international Conference on Multimedia Analysis and pattern recognition, MAPR 2024

作者： Bao, Pham thai thu Hien, Do thi Cam, Nguyen Tan Pham, Van-Hau University of Information Technology Information Security Laboratory Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350368437

When Windows becomes the most widely used operating system compared to its counterparts, there is a rising number of attacks targeting this system, in which malicious executable files or malware is one of the most prevalent threats. Hence, verifying the maliciousness of executable files is essential to prevent harmful impacts on the system, leading to numerous research efforts to propose novel Windows malware detection methods. Although machine learning (ML) or deep learning (DL) has offered promising results in detecting malware, existing works still have limitations, such as using static analysis methods or only leveraging a piece of specific information to recognize maliciousness. this may reduce the effectiveness of the detector while dealing with malware that uses evasion techniques. therefore, in this paper, we present a multimodal approach for Windows malware detection based on various pieces of information extracted by a hybrid analysis process. While the PE header information plays the role of static features, we aim to extract a dynamic control flow graph (CFG). We utilize the dynamic analysis method to create CFG, through the symbolic execution approach, with the intent that our work can be applied to certain malware environments that may undergo code obfuscation. the experiments on approximately 24,000 PE files in multiple datasets prove the effectiveness of our work, with an accuracy of 99.25% in distinguishing malware and benign files. © 2024 IEEE.

关键词： deep learning hybrid analysis Malware detection multimodal

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Construction of combinatorial pyramids

Construction of combinatorial pyramids

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4th IAPR international workshop on graph based representations in pattern recognition, GbRPR 2003

作者： Brun, Luc Kropatsch, Walter G. Université de Reims France Institute for Computer-aided Automation Pattern Recognition and Image Processing Group Vienna Univ. of Technology Austria

ISBN: (纸本)354040452X

Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Each vertex of a reduced graph corresponds to a connected set of vertices in the level below. One connected set of vertices reduced into a single vertex at the above level is called the reduction window of this vertex. In the same way, a connected set of vertices in the base level graph reduced to a single vertex at a given level is called the receptive field of this vertex. the graphs used in the pyramid may be region adjacency graphs, dual graphs or combinatorial maps. this last type of pyramids are called Combinatorial Pyramids. Compared to usual graph data structures, combinatorial maps encode one graph and its dual within a same formalism and offer an explicit encoding of the orientation of edges around vertices. this paper describes the construction scheme of a Combinatorial Pyramid. We also provide a constructive definition of the notions of reduction windows and receptive fields within the Combinatorial Pyramid framework. © Springer-Verlag Berlin Heidelberg 2003.

关键词： graphic methods

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Reducing the Computational Complexity of the Eccentricity Transform of a Tree 13th

Reducing the Computational Complexity of the Eccentricity...

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13th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2023

作者： Banaeyan, Majid Kropatsch, Walter G. Pattern Recognition and Image Processing Group TU Wien Vienna Austria

ISBN: (纸本)9783031427947

this paper proposes a novel approach to reduce the computational complexity of the eccentricity transform (ECC) for graph-based representation and analysis of shapes. the ECC assigns to each point within a shape its geodesic distance to the furthest point, providing essential information about the shape’s geometry, connectivity, and topology. Although the ECC has proven valuable in numerous applications, its computation using traditional methods involves heavy computational complexity. To overcome this limitation, we present a method that computes the ECC of a tree, significantly reducing the computational complexity from O(n2log(n) ) to O(b), where n and b are the numbers of vertices and branching points in the tree, respectively. Our method begins by computing the ECC for tree structures, which are simpler representations of shapes. Subsequently, we introduce the concept of a 3D curve that corresponds to a smooth shape without holes, enabling the computation of the ECC for more complex shapes. By leveraging the 3D curve representation, our method provides an upper-bound approximation of the ECC, which can be effectively utilized in various applications. the proposed approach not only preserves the valuable properties of the ECC but also significantly reduces the computational burden, making it a more efficient and practical solution for graph-based representation and analysis of shapes in both 2D and 3D contexts. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational complexity

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pattern recognition Strategies to Classify Traced Neurons 7th

Pattern Recognition Strategies to Classify Traced Neurons

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7th international workshop on Artificial Intelligence and pattern recognition (IWAIPR)

作者： Lopez-Cabrera, Jose D. Hernandez-Perez, Leonardo A. Lorenzo-Ginori, Juan, V Univ Cent Marta Abreu Las Villas Informat Res Ctr Santa Clara 54830 Cuba Empresa Telecomunicac Cuba SA Santa Clara Cuba

ISBN: (纸本)9783030896911;9783030896904

this paper addresses two strategies for pattern recognition in high-dimension data sets, obtained from databases of digitally traced neurons. the first strategy has as distinctive characteristic that the features are obtained both from the whole neuron and from the axon and the dendrites as well. On the other hand, the second strategy is based in feature extraction from data sequences obtained from the decomposition of the traced neuron. Both strategies generate a wide variety of datawhich result in highly dimensional data sets. Two supervised pattern recognition alternatives were implemented for feature selection. When using the first strategy, the percentage of correctly classified cases raised up to 94.55% once the fusion of data extraction alternatives is performed and the feature selection methods are applied. these results are maintained for three different sets of traced neurons pertaining different regions of the cerebral cortex. By means of the second strategy, a group or recursive feature elimination alternatives was evaluated. Using this strategy, the mean percentage of correctly classified cases achieved was 78.5% and 76.79% which are comparable to those obtained using multiple iterations and the computational time was reduced three to four times. the results obtained encourage the use of the proposed strategies to reduce the dimensionality of the data sets obtained from the traced neurons.

关键词： Feature selection pattern recognition Neuron classification Traced neurons

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the use of graph theory in the implementation of psychodiagnostic projects on the example of researching the leadership qualities of participants in software development teams 7

The use of graph theory in the implementation of psychodiagn...

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7th international Conference "Information Technology and Interactions", IT and I 2020

作者： Lukianov, Dmytro Radyuk, Oleg Charniauskaya, Hanna Basinskaya, Irina Interdisciplinary Institute for Advanced Studies and Retraining Belarusian National Technical University 77 Partyzansky ave. Minsk220107 Belarus Individual Entrepreneur Post office box 67 Minsk-134220134 Belarus HR in IT Rogachyovskaya str. 7-36 Minsk220056 Belarus Belarusian State University 4 Nezavisimosti Avenue Minsk220030 Belarus

the article proposes consider the application of visual analysis of psychological testing results through the use of directed graph representations. It is proposed to consider the method of visual analysis by means of various representations based on the analysis of the number of connections between the elements of the system, considered as the basis for the formation of a directed graph. In the example considered in the article, it is proposed to consider the scales of the integrated test technique used as the vertices of the graph. As the main views, the application of calculating centrality properties based on the number of links, the topological structure of links, and the Page Rank parameter is demonstrated. It is proposed to use the method of visual analysis of the graph as an additional to the classical method of correlation analysis used in processing the results of the application of psychodiagnostic methods. the possibility of using visual analysis to form hypotheses about the possible optimization of the structure of the scales used in the design of psychodiagnostic techniques (test batteries) is shown. In parallel, the results of the analysis of the leadership qualities of such a category of specialists as software developers (members of development teams) are presented. © 2020 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： Directed graphs

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