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Dynamic weighted fusion of adaptive classifier ensembles based on changing data streams 6

6th iapr TC3 international Workshop on Artificial Neural Networks for pattern recognition, ANNPR 2014

作者： Pagano, Christophe Granger, Eric Sabourin, Robert Marcialis, Gian Luca Roli, Fabio Laboratoire d’imagerie de vision et d’intelligence artificielle École de technologie supérieure Université du Québec Montreal Canada Pattern Recognition and Applications Group Dept. Of Electrical and Electronic Engineering University of Cagliari Cagliari Italy

ISBN: (纸本)9783319116556

Adapting classification systems according to new input data streams raises several challenges in changing environments. Although several adaptive ensemble-based strategies have been proposed to preserve previously-acquired knowledge and reduce knowledge corruption, the fusion of multiple classifiers trained to represent different concepts can increase the uncertainty in prediction level, since only a sub-set of all classifier may be relevant. In this paper, a new score-level fusion technique, called Swavgh, is proposed where each classifier is dynamically weighted according to the similarity between an input pattern and the histogram representation of each concept present in the ensemble. During operations, the Hellinger distance between an input and the histogram representation of every previously-learned concept is computed, and the score of every classifier is weighted dynamically according to the resemblance to the underlying concept distribution. Simulation produced with synthetic problems indicate that the proposed fusion technique is able to increase system performance when input data streams incorporate abrupt concept changes, yet maintains a level of performance that is comparable to the average fusion rule when the changes are more gradual. © Springer international Publishing Switzerland 2014.

关键词： Graphic methods

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Introducing an experimental framework in C# for fingerprint recognition

Introducing an experimental framework in C# for fingerprint ...

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6th Mexican conference on pattern recognition, MCPR 2014

作者： Medina-Pérez, Miguel Angel Loyola-González, Octavio Gutierrez-Rodríguez, Andres Eduardo García-Borroto, Milton Altamirano-Robles, Leopoldo Instituto Nacional de Astrofísica Óptica Y Electrónica Luis Enrique Erro No. 1 Sta. María Tonanzintla Puebla C.P. 72840 Mexico Centro de Bioplantas Universidad de Ciego de Ávila Carretera a Morón km 9 Ciego de Ávila Cuba Instituto Superior Politécnico José A. Echeverría C. 114 No. 11901 e/ Ciclovia y Rotonda Apdo. 6028 Marianao Habana Cuba

ISBN: (纸本)9783319074900

In this paper, a framework for fingerprint recognition is introduced. the framework contains several algorithms for fingerprint matching and feature extraction, as well as the evaluation protocol for several fingerprint verification competitions. All the algorithms are implemented in C# providing the source code which researchers can review, reuse or modify. In order to show the framework relevance, an experimental comparison among different matching algorithms is presented. © 2014 Springer international Publishing.

关键词： pattern matching

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U-stroke pattern modeling for end user identity verification through ubiquitous input device

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in bioinformatics) 2015年 9339卷 219-230页

作者： Bhattasali, Tapalina Chaki, Nabendu Saeed, Khalid Chaki, Rituparna Department of Computer Science and Engineering University of Calcutta Kolkata India Bialystok University of Technology Bialystok Poland A.K.Choudhury School of Information Technology University of Calcutta Kolkata India

ISBN: (纸本)9783319243689

Identity verification on ubiquitous input devices is a major concern to validate end-users, because of mobility of the devices. User device interaction (UDI) is capable to capture end-users’ behavioral nature from their device usage pattern. the primary goal of this paper is to collect heterogeneous parameters of usage patterns from any device and build personal profile with good-recognition capability. this work mainly focuses on finding multiple features captured from the usage of smart devices;so that parameters could be used to compose hybrid profile to verify end-users accurately. In this paper, U-Stroke modeling is proposed to capture behavioral data mainly from smart input devices in ubiquitous environment. In addition to this, concept of CCDA (capture, checking, decision, and action) model is proposed to process U-Stroke data efficiently to verify enduser’s identity. this proposal can draw attention of many researchers working on this domain to extend their research towards this direction. © IFIP international Federation for Information Processing 2015.

关键词： Touch screens

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FFT algorithm of complex exponent moments and its application in image recognition

FFT algorithm of complex exponent moments and its applicatio...

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6th international conference on Digital Image Processing (ICDIP)

作者： Ping, Ziliang Jiang, Yongjing Zhou, Suhua Wu, Yu Inner Mongolia Normal Univ Phys & Elect Coll Hohhot 010022 Peoples R China Beijing Univ Posts & Telecommun Century Coll Beijing Peoples R China

ISBN: (纸本)9781628411867

Orthogonal multi-distorted invariant Complex Exponent Moments (CEMs) are proposed. A fast and accurate 2-D Fast Fourier Transform (FFT) algorithm is used to calculate CEMs. theoretical analysis is presented to demonstrate the multi-distorted invariant property of CEMs. the proposed method is applied in the pattern recognition of human faces, English letters and Chinese characters. Experimental results show that CEMs have higher quality and lower computational complexity than RHFMs in image reconstruction and pattern recognition.

关键词： Complex Exponent Moments FFT algorithm Multi-distorted invariance pattern recognition

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Logol: Expressive pattern Matching in Sequences. Application to Ribosomal Frameshift Modeling

Logol: Expressive Pattern Matching in Sequences. Application...

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9th iapr international conference on pattern recognition in bioinformatics (PRIB)

作者： Belleannee, Catherine Sallou, Olivier Nicolas, Jacques Univ Rennes 1 Irisa Inria F-35042 Rennes France

ISBN: (纸本)9783319091921;9783319091914

Most of the current practice of pattern matching tools is oriented towards finding efficient ways to compare sequences. this is useful but insufficient: as the knowledge and understanding of some functional or structural aspects of living systems improve, analysts in molecular biology progressively shift from mere classification tasks to modeling tasks. People need to be able to express global sequence architectures and check various hypotheses on the way their sequences are structured. It appears necessary to offer generic tools for this task, allowing to build more expressive models of biological sequence families, on the basis of their content and structure. this article introduces Logol, a new application designed to achieve pattern matching in possibly large sequences with customized biological patterns. Logol consists in both a language for describing patterns, and the associated parser for effective pattern search in sequences (RNA, DNA or protein) with such patterns. the Logol language, based on an high level grammatical formalism, allows to express flexible patterns (with mispairings and indels) composed of both sequential elements (such as motifs) and structural elements (such as repeats or pseudoknots). Its expressive power is presented through an application using the main components of the language : the identification of -1 programmed ribosomal frameshifting (PRF) events in messenger RNA sequences. Logol allows the design of sophisticated patterns, and their search in large nucleic or amino acid sequences. It is available on the GenOuest bioinformatics platform at http://***. the core application is a command-line application, available for different operating systems. the Logol suite also includes interfaces, e. g. an interface for graphically drawing the pattern.

关键词： Molecular biology

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Robust Non-Parametric Probabilistic Image Processing for Face recognition and pattern recognition

Robust Non-Parametric Probabilistic Image Processing for Fac...

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6th international conference on Digital Image Processing (ICDIP)

作者： Meropi, Pavlidou Zioutas, George Aristotle Univ Thessaloniki Dept Elect Engn Thessaloniki Greece

ISBN: (纸本)9781628411867

Face recognition has been a pattern recognition application of great interest. Many mathematical models have been used for face recognition and among them probabilistic methods However, up to now probabilistic methods rely heavily on the number of training data and do not fully exploit the 2-dimensional information of the images, both the training and the testing sets. In this paper's method a new 2-D robust probabilistic method of transforming the principal components of the initial image data, allowing support vector machines to efficiently capture the inference between images. this new algorithm encodes every image with the help of Robust Kernel non Parametric Estimation and in the second stage uses Support Vector Machines to classify this encoded information. Results exhibit that Non Parametric Estimation of the Probability Function of the image highlights the unique characteristics of each person making it easier for classifiers to group those instances and efficiently perform the classification of the images and thus leading to better results compared to up to date methods for face recognition.

关键词： robust classification face recognition support vector machines pattern recognition kernel density estimation

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Open-lexicon Language Modeling Combining Word and Character Levels 14

Open-lexicon Language Modeling Combining Word and Character ...

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14th international conference on Frontiers in Handwriting recognition (ICFHR)

作者： Kozielski, Michal Matysiak, Martin Doetsch, Patrick Schlueter, Ralf Ney, Hermann Rhein Westfal TH Aachen Chair Comp Sci 6 Human Language Technol & Pattern Recognit Grp D-52056 Aachen Germany

ISBN: (纸本)9781479943357

In this paper we investigate different a-gram language models that are defined over an open lexicon. We introduce a character-level language model and combine it with a standard word-level language model in a backoff fashion. the character-level language model is redefined and renormalized to assign zero probability to words from a fixed vocabulary. Furthermore we present a way to interpolate language models created at the word and character levels. the computation of character-level probabilities incorporates the across-word context. We compare perplexities on all words from the test set and on in-lexicon and OOV words separately on corpora of English and Arabic text.

关键词： Computational modeling Context Interpolation Speech recognition Standards Training Vocabulary modelling languages Speech recognition Interpolation Computational modeling Vocabulary Word Functional training TEST SETS Training

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NEW HUMAN BODY SHAPE DESCRIPTOR BASED ON ANthROPOMETRICS POINTS 6

NEW HUMAN BODY SHAPE DESCRIPTOR BASED ON ANTHROPOMETRICS POI...

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6th international conference on Soft Computing and pattern recognition (SoCPaR)

作者： Hamad, Moez thomassey, Sebastien Bruniaux, Pascal Univ Lille North France GEMTEX ENSAIT Lille France

ISBN: (纸本)9781479959341

this paper will focus on the issue of human body dissimilarity detection from 3D bodyscan. A new 3D human body shape descriptor is proposed as well as a global geometric shape analysis of body shape surfaces coupled with anthropometrics points. the aim of this research is then to establish a new methodology of human body morphology shapes detection in order to define the morphotypes of a given population. A computation of the geodesic distributions based on anthropometrics feature points for human torso provides quantitative information about their similarities. the Euclidean distance is the metric used for the comparison of the shape descriptors. the k-means clustering technique is then implemented to define the most relevant morphologies. Our methodology is then evaluated on 3D scan database of 53 female. the study may be attracted for further researchers from several research communities including pattern recognition, computer graphics, computer vision, anthropometry, human morphology, data analysis and mass customization.

关键词： 3D shape descriptor body scanner 3D CAD system pattern recognition geodesic distributions

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Person Attributes Extraction in Profiles Based on SVM and pattern

Person Attributes Extraction in Profiles Based on SVM and Pa...

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2015 6th IEEE international conference on Software Engineering and Service Science(ICSESS 2015)

作者： Zhen Zhu Yuan Sun School of Information Engineering Minzu University of China

this paper is an exploration to find a way to get the person attributes in profiles. Considering those attributes exists in large volume of unstructured data, and it is very difficult to gain in a short time. So, we use a method combing the pattern and SVM to extract the person attributes. Firstly, we collect many raw profiles in websites by our configurable crawler. Secondly, we use statistic methods to do pre-processing works include lexical analysis and name recognition. thirdly, we build the patterns, which can use in model to extract the person attributes. Also we generalize those patterns to SVM features. Finally, we use SVM assisted with pattern-based method to predict the person attributes. the results prove the method is effective and the data we extracted is useful in building specificareas' expert database and information retrieval.

关键词： Person attributes extraction Expert database SVM pattern-based extraction

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Working Condition recognition of Cement Decomposition Furnace Based on ART-2 Neural Network

Working Condition Recognition of Cement Decomposition Furnac...

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6th international conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Song Qiuyun Yuan Zhugang Univ Jinan Jinan 250022 Shandong Peoples R China

ISBN: (纸本)9781479934348

this paper advances a two-stage ART-2 neural network method on working condition recognition of cement decomposition furnace. the process parameters describing cement decomposition furnace conditions are determined based on the process design requirements and the analysis of field operation experience. the field operating datas through mean filtering are determined as the first-class ART-2 network inputs, and the trend recognitions of the parameters are finished based on the trend recognition function. the results are determined as the second-class ART-2 network inputs, and the real time recognitions of decomposition furnace conditions are completed using the pattern recognition function. the simulation and practical operation show the effectiveness of the method.

关键词： Cement Decomposition Furnace Working Condition recognition ART-2 Neural Network Trend recognition pattern recognition

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