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检索条件"任意字段=3rd IAPR International Conference on Pattern Recognition in Bioinformatics"

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An improved MOBIL descriptor for markerless augmented reality

An improved MOBIL descriptor for markerless augmented realit...

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international conference on Control, Engineering & Information Technology (CEIT)

作者： Abdelkader Bellarbi Nadia Zenati-Henda Hayet Belghit Mahfoud Hamidia Samir Benbelkacem Samir Otmane CDTAAlgiers Algeria IBISC Lab University of Evry France Centre de Developpement des Technologies Avancees Algiers DZ

In this paper, we present an improved version of MOBIL descriptor [1] (Improved MOments based BInary differences for Local description), which introduces two main contributions. The first one is the use of geometric information for the binary test instead of the classical intensity binary test, to get more precision in the description step. The second one is to attribute two bits for each test, to increase the distinctiveness level. This approach offers high distinctiveness against affine transformations and appearance changes. The experimental evaluation shows that MOBIL achieves a quite good performance in term of low computation complexity and high recognition rate compared to state-of-the-art real-time local descriptors.

关键词： Robustness Computer vision Augmented reality pattern recognition conferences Feature extraction Image recognition

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A Novel Behavior-based Tracking Attack for User Identification 3

A Novel Behavior-based Tracking Attack for User Identificati...

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3rd international conference on Advanced Cloud and Big Data (CBD)

作者： Gu, Xiaodan Yang, Ming Fei, Jiaxuan Ling, Zhen Luo, Junzhou Southeast Univ Sch Comp Sci & Engn Nanjing Jiangsu Peoples R China State Grid Smart Grid Res Inst Beijing Peoples R China

ISBN: (纸本)9781467385374

Currently, people around the world daily use the Internet to access various services, such as, email and online shopping. However, the behavior-based tracking attacks have posed a considerable threat to users' privacy. Relying on characteristic patterns within the Internet activities, this attack can link a user's multiple sessions which are composed of a period of user's traffic. Once a user's personally identifiable information is disclosed in some session, the attacker can obtain the user's other network activities according to the linked sessions. In this paper, we investigate this behavior-based tracking attack and discuss the possible countermeasures. We preprocess the raw traffic data and then extract features ranging from lower layer network packets to high level application related traffic. Specifically, we focuses on four types of application-level traffic to infer users' habits, including HTTP, IM, Email, and P2P. A Multinomial Naive Bayes Classifier is employed to correlate users' sessions in distinct period. To evaluate the feasibility of our approach, we collect traffic in real-world environment to construct two distinct sizes of datasets. In the first dataset, we have 55 users' traffic during five weeks and the accuracy of our approach could reach 100%. To further illustrate the scalability of this approach, 509 users are selected from the second dataset in terms of the user's active degree. Finally, we can correctly correlate average 85.61% instances. Our extensive empirical experiments demonstrate the effectiveness and efficiency of our approach.

关键词： behavior-based tracking traffic analysis pattern recognition privacy

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SFFS-SW: A Feature Selection Algorithm Exploring the Small-World Properties of GNs

SFFS-SW: A Feature Selection Algorithm Exploring the Small-W...

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

作者： da Rocha Vicente, Fabio Fernandes Lopes, Fabricio Martins Fed Univ Technol Curitiba Parana Brazil

ISBN: (纸本)9783319091921;9783319091914

In recent years, several methods for gene networks (GNs) inference from expression data have been developed. Also, models of data integration (as protein-protein and protein-DNA) are nowadays broadly used to face the problem of few amount of expression data. Moreover, it is well known that biological networks conserve some topological properties. The small-world topology is a common arrangement in nature found both in biological and non-biological phenomena. However, in general this information is not used by GNs inference methods. In this work we proposed a new GNs inference algorithm that combines topological features and expression data. The algorithm outperforms the approach that uses only expression data both in accuracy and measures of recovered network.

关键词： small-world gene networks feature selection graph theory pattern recognition bioinformatics

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Fundamental Study for Verbalization of Embodied Expertise based on pattern recognition 3

Fundamental Study for Verbalization of Embodied Expertise ba...

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3rd IIAI international conference on Advanced Applied Informatics (IIAI-AAI)

作者： Hojo, Hiroki Nomachi, Nozomi Tomoto, Yutaro Nakamura, Tsuyoshi Kanoh, Masayoshi Yamada, Koji Nagoya Inst Technol Nagoya Aichi Japan Chukyo Univ Nagoya Aichi Japan Inst Adv Media Arts & Sci Ogaki Gifu Japan

ISBN: (纸本)9781479941735

Embodied expertise, which expresses skills of experts, is a kind of tacit knowledge that is difficult to transfer from one person to another by writing it down or verbalizing it. The aim of our study is to translate embodied expertise into explicit knowledge, i.e. onomatopoeias. We call the onomatopoeias "embodied expertise onomatopoeias", which can enable people to understand the skills intuitively and easily. Acquiring embodied expertise onomatopoeias is considered as a problem of pattern recognition. Our study focused on the skills of Japanese penmanship, Pen Shodo, which is Japanese calligraphy using a pen, to translate tacit knowledge into onomatopoeias and investigated the possibility of constructing a training system for these skills.

关键词： Embodied Expertise Onomatopoeias pattern recognition Verbalization

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A Benchmark Study of Large-scale Unconstrained Face recognition 2

A Benchmark Study of Large-scale Unconstrained Face Recognit...

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IEEE/iapr international Joint conference on Biometrics (IJCB)

作者： Liao, Shengcai Lei, Zhen Yi, Dong Li, Stan Z. Chinese Acad Sci Inst Automat Ctr Biometr & Secur Res 95 Zhongguancun East Rd Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China

ISBN: (纸本)9781479935840

Many efforts have been made in recent years to tackle the unconstrained face recognition challenge. For the benchmark of this challenge, the Labeled Faces in the Wild (LFW) database has been widely used. However, the standard LFW protocol is very limited, with only 3,000 genuine and 3,000 impostor matches for classification. Today a 97% accuracy can be achieved with this benchmark, remaining a very limited room for algorithm development. However, we argue that this accuracy may be too optimistic because the underlying false accept rate may still be high (e.g. 3%). Furthermore, performance evaluation at low FARs is not statistically sound by the standard protocol due to the limited number of impostor matches. Thereby we develop a new benchmark protocol to fully exploit all the 13,233 LFW face images for large-scale unconstrained face recognition evaluation under both verification and open-set identification scenarios, with a focus at low FARs. Based on the new benchmark, we evaluate 21 face recognition approaches by combining 3 kinds of features and 7 learning algorithms. The benchmark results show that the best algorithm achieves 41.66% verification rates at FAR=0.1%, and 18.07% open-set identification rates at rank 1 and FAR=1%. Accordingly we conclude that the large-scale unconstrained face recognition problem is still largely unresolved, thus further attention and effort is needed in developing effective feature representations and learning algorithms. We thereby release a benchmark tool to advance research in this field.

关键词： Face 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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Application of Multidimensional Data Visualization in Creation of pattern recognition Systems 3

Application of Multidimensional Data Visualization in Creati...

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3rd international conference on Man-Machine Interactions (ICMMI)

作者： Jamroz, Dariusz AGH Univ Sci & Technol PL-30059 Krakow Poland

ISBN: (纸本)9783319023090

The paper presents the application of multidimensional data visualization to obtain the views of 5-dimensional space of features created by recognition of printed characters. On the basis of these views it was stated that the features chosen to construction of features space are sufficient to correct recognition process. This is the significant help by constructing the recognition systems because the correct selection of objects properties on the basis of which the recognition should occur is one of the hardest stages.

关键词： multidimensional visualization pattern recognition

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IEEE/iapr international Joint conference on Biometrics (IJCB)

作者： Khanyile, Nontokozo P. de Kock, Antonie Mathekga, Mmamolatelo E. CSIR Meiring Naudea Rd Pretoria South Africa

ISBN: (纸本)9781479935840

This paper identifies and analyses the factors that contribute to the similarity between two sets of minutiae points as well as the probability that two sets of minutiae points were extracted from fingerprints of the same finger. Minutiae-based fingerprint matching has been studied extensively in the literature, however, there is still a need for major improvement especially when it comes to comparing partial fingerprints. This paper looks at existing similarity measures;discusses their performance at discriminating between minutiae points from fingerprints of the same finger and of different fingers. The matching problem has been broken down into smaller subproblems which are easier to define and solve. Each of the scores discussed are analyzed and tested to see if they are able to deal with each of the matching subproblems. Results show that most scores in the literature fall in one of two ends of matching;good at discriminating impostor matches, or good at discriminating genuine matches. The authors propose a score which bridges these two types of scores and enables optimal impostor and genuine comparisons.

关键词： pattern matching

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ICPRAM 2014 - Proceedings of the 3rd international conference on pattern recognition Applications and Methods

ICPRAM 2014 - Proceedings of the 3rd International Conferenc...

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3rd international conference on pattern recognition Applications and Methods, ICPRAM 2014

ISBN: (纸本)9789897580185

The proceedings contain 104 papers. The topics discussed include: multiple segmentation of image stacks;measuring cluster similarity by the travel time between data points;affine invariant shape matching using histogram of radon transform and angle correlation matrix;unsupervised consensus functions applied to ensemble biclustering;modified fuzzy C-means as a stereo segmentation method;on selecting helpful unlabeled data for improving semi-supervised support vector machines;SCHOG feature for pedestrian detection;discriminative prior bias learning for pattern classification;minutiae persistence among multiple samples of the same person's fingerprint in a cooperative user scenario;dirichlet-tree distribution enhanced random forests for head pose estimation;and a descriptor based on intensity binning for image matching.

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Research on bioinformatics with Sparse Feature Fusion for Object recognition

Research on Bioinformatics with Sparse Feature Fusion for Ob...

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3rd international conference on Material Engineering, Chemistry, bioinformatics (MECB 2013)

作者： Wu, ShuFang Zhu, Jie Zhang, ZhaoFeng Hebei Software Inst Dept Informat Engn Baoding Hebei Peoples R China Hebei Univ Coll Management Baoding Peoples R China Cent Inst Correct Police Dept Informat Management Beijing Peoples R China

ISBN: (纸本)9783037859148

Combining multiple bioinformatics such as shape and color is a challenging task in object recognition. Usually, we believe that if more different bioinformatics are considered in object recognition, then we could get better result. Bag-of-words-based image representation is one of the most relevant approaches;many feature fusion methods are based on this model. Sparse coding has attracted a considerable amount of attention in many domains. A novel sparse feature fusion algorithm is proposed to fuse multiple bioinformatics to represent the images. Experimental results show good performance of the proposed algorithm.

关键词： feature fusion sparse coding object recognition

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